PATENT DOCUMENT

Publication Number: US-10671428-B2
Application Number: US-201615166090-A
Country: US
Kind Code: B2

Title: Distributed personal assistant

Abstract:
An exemplary method for using a virtual assistant may include, at an electronic device configured to transmit and receive data, receiving a user request for a service from a virtual assistant; determining at least one task to perform in response to the user request; estimating at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimating, determining whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, causing the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generating executable code for carrying out the least one task; and transmitting the executable code from the electronic device.

Claims:
What is claimed is: 
     
       1. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device, cause the electronic device to:
 receive a user request for a service from a virtual assistant; 
 determine at least one task to perform in response to the user request; 
 estimate at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic of a plurality of heuristics, wherein estimating the at least one performance characteristic based on the at least one heuristic of the plurality of heuristics comprises:
 determining whether performing the at least one task requires using personal data stored on the electronic device; 
 in response to determining that performing the at least one task requires using personal data stored on the electronic device, identifying a first heuristic of the plurality of heuristics; 
 weighting a second heuristic of the plurality of heuristics relative to one or more other heuristics of the plurality of heuristics based on a first weight, wherein a value of the first weight is determined based on computing conditions associated with the electronic device; and 
 estimating the at least one performance characteristic based on the first heuristic and the weighted second heuristic; 
 
 based on the estimate, determine whether to execute the at least one task at the electronic device using the personal data; 
 in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; and 
 in accordance with a determination to execute the at least one task outside the electronic device:
 generate executable code for carrying out the at least one task; and 
 transmit the executable code from the electronic device. 
 
 
     
     
       2. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes the battery life of the electronic device. 
     
     
       3. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes availability at the electronic device of high-frequency wireless networking service compliant with the IEEE 802.11x standard. 
     
     
       4. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes network speed available to the electronic device. 
     
     
       5. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes available memory space of the electronic device. 
     
     
       6. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes processing speed of the electronic device. 
     
     
       7. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes the operating system of the electronic device. 
     
     
       8. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes available cache space at the electronic device. 
     
     
       9. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes the type of electronic device. 
     
     
       10. The non-transitory computer-readable storage medium of  claim 1 , wherein the first heuristic includes privacy settings associated with the at least one task. 
     
     
       11. The non-transitory computer-readable storage medium of  claim 1 , wherein the first heuristic includes data transmission restrictions associated with the at least one task. 
     
     
       12. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes a location of the electronic device. 
     
     
       13. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes the characteristics of the at least one task. 
     
     
       14. The non-transitory computer-readable storage medium of  claim 1 , wherein the second heuristic includes user preferences associated with the task. 
     
     
       15. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes context resolution. 
     
     
       16. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes speech recognition. 
     
     
       17. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes automatic speech recognition. 
     
     
       18. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes domain classification. 
     
     
       19. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes natural language parsing. 
     
     
       20. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes query resolution. 
     
     
       21. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes natural language synthesis. 
     
     
       22. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes user interface resolution. 
     
     
       23. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one task includes text-to-speech conversion. 
     
     
       24. The non-transitory computer-readable storage medium of  claim 1 , further comprising:
 in response to the transmitting, receiving, at the electronic device, information associated with execution of the executable code. 
 
     
     
       25. The non-transitory computer-readable storage medium of  claim 1 , further comprising, after the causing the execution, transmitting from the electronic device the results of the causing the execution. 
     
     
       26. The non-transitory computer-readable storage medium of  claim 1 , wherein the one or more programs comprise further instructions that cause the electronic device to:
 estimate one or more performance characteristics for completion of at least two additional discrete tasks; and 
 determine, based on the estimating of the one or more performance characteristics for completion of the at least two additional discrete tasks, whether to execute the at least two additional discrete tasks at the electronic device or at a second electronic device. 
 
     
     
       27. The non-transitory computer-readable storage medium of  claim 1 , wherein the causing the execution further comprises:
 storing executable code on the electronic device; 
 wherein the causing the execution includes causing the execution of the stored code on the electronic device. 
 
     
     
       28. The non-transitory computer-readable storage medium of  claim 1 , wherein the user request is in unstructured natural language format. 
     
     
       29. The non-transitory computer-readable storage medium of  claim 1 , wherein the at least one performance characteristic includes an estimated duration to complete the at least one task. 
     
     
       30. The non-transitory computer-readable storage medium of  claim 1 , wherein the virtual assistant is distributed between the electronic device and a server, and wherein transmitting the executable code comprises transmitting the executable code to the server. 
     
     
       31. The non-transitory computer-readable storage medium of  claim 1 , wherein transmitting the executable code comprises transmitting the executable code to a second electronic device. 
     
     
       32. The non-transitory computer-readable storage medium of  claim 31 , wherein the second electronic device is connected to the electronic device over a local network. 
     
     
       33. The non-transitory computer-readable storage medium of  claim 1 , wherein transmitting the executable code comprises transmitting the executable code to a second electronic device;
 further comprising fulfilling the user request at the second electronic device. 
 
     
     
       34. The non-transitory computer-readable storage medium of  claim 1 , wherein the executable code enables a determination of whether information required for executing the at least one task is available to the virtual assistant. 
     
     
       35. A method of using a virtual assistant, comprising:
 at an electronic device configured to transmit and receive data, 
 receiving a user request for a service from a virtual assistant; 
 determining at least one task to perform in response to the user request; 
 estimating at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic of a plurality of heuristics, wherein estimating the at least one performance characteristic based on the at least one heuristic of the plurality of heuristics comprises:
 determining whether performing the at least one task requires using personal data stored on the electronic device; 
 in response to determining that performing the at least one task requires using personal data stored on the electronic device, identifying a first heuristic of the plurality of heuristics; 
 weighting a second heuristic of the plurality of heuristics relative to one or more other heuristics of the plurality of heuristics based on a first weight, wherein a value of the first weight is determined based on computing conditions associated with the electronic device; and 
 estimating the at least one performance characteristic based on the first heuristic and the weighted second heuristic; 
 
 based on the estimating, determining whether to execute the at least one task at the electronic device; 
 in accordance with a determination to execute the at least one task at the electronic device, causing the execution of the at least one task at the electronic device using the personal data; and 
 in accordance with a determination to execute the at least one task outside the electronic device:
 generating executable code for carrying out the at least one task; and 
 transmitting the executable code from the electronic device. 
 
 
     
     
       36. The method of  claim 35 , further comprising:
 in response to the transmitting, receiving, at the electronic device, information associated with execution of the executable code. 
 
     
     
       37. The method of  claim 35 , further comprising, after the causing the execution, transmitting from the electronic device the results of the causing the execution. 
     
     
       38. The method of  claim 35 , further comprising:
 estimating one or more performance characteristics for completion of at least two additional discrete tasks; and 
 determining, based on the estimating of the one or more performance characteristics for completion of the at least two additional discrete tasks, whether to execute the at least two additional discrete tasks at the electronic device or at a second electronic device. 
 
     
     
       39. The method of  claim 35 , wherein the causing the execution further comprises:
 storing executable code on the electronic device; 
 wherein the causing the execution includes causing the execution of the stored code on the electronic device. 
 
     
     
       40. The method of  claim 35 , wherein the user request is in unstructured natural language format. 
     
     
       41. The method of  claim 35 , wherein the virtual assistant is distributed between the electronic device and a server, and wherein transmitting the executable code comprises transmitting the executable code to the server. 
     
     
       42. The method of  claim 35 , wherein transmitting the executable code comprises transmitting the executable code to a second electronic device. 
     
     
       43. The method of  claim 42 , wherein the second electronic device is connected to the electronic device over a local network. 
     
     
       44. The method of  claim 35 , wherein transmitting the executable code comprises transmitting the executable code to a second electronic device;
 further comprising fulfilling the user request at the second electronic device. 
 
     
     
       45. The method of  claim 35 , wherein the executable code enables a determination of whether information required for executing the at least one task is available to the virtual assistant. 
     
     
       46. An electronic device, comprising:
 one or more processors; 
 a memory; and 
 one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
 receiving a user request for a service from a virtual assistant; 
 determining at least one task to perform in response to the user request; 
 estimating at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic of a plurality of heuristics, wherein estimating the at least one performance characteristic based on the at least one heuristic of the plurality of heuristics comprises:
 determining whether performing the at least one task requires using personal data stored on the electronic device; 
 in response to determining that performing the at least one task requires using personal data stored on the electronic device, identifying a first heuristic of the plurality of heuristics; 
 weighting a second heuristic of the plurality of heuristics relative to one or more other heuristics of the plurality of heuristics based on a first weight, wherein a value of the first weight is determined based on computing conditions associated with the electronic device; and 
 estimating the at least one performance characteristic based on the first heuristic and the weighted second heuristic; 
 
 based on the estimating, determining whether to execute the at least one task at the electronic device; 
 in accordance with a determination to execute the at least one task at the electronic device, causing the execution of the at least one task at the electronic device using the personal data; and 
 in accordance with a determination to execute the at least one task outside the electronic device:
 generating executable code for carrying out the at least one task; and 
 transmitting the executable code from the electronic device. 
 
 
 
     
     
       47. The electronic device of  claim 46 , wherein the one or more programs comprise further instructions for:
 in response to the transmitting, receiving, at the electronic device, information associated with execution of the executable code. 
 
     
     
       48. The electronic device of  claim 46 , wherein the one or more programs comprise further instructions for, after the causing the execution, transmitting from the electronic device the results of the causing the execution. 
     
     
       49. The electronic device of  claim 46 , further comprising:
 estimating one or more performance characteristics for completion of at least two additional discrete tasks; and 
 determining, based on the estimating of the one or more performance characteristics for completion of the at least two additional discrete tasks, whether to execute the at least two additional discrete tasks at the electronic device or at a second electronic device. 
 
     
     
       50. The electronic device of  claim 46 , wherein the causing the execution further comprises:
 storing executable code on the electronic device; 
 wherein the causing the execution includes causing the execution of the stored code on the electronic device. 
 
     
     
       51. The electronic device of  claim 46 , wherein the user request is in unstructured natural language format. 
     
     
       52. The electronic device of  claim 46 , wherein the virtual assistant is distributed between the electronic device and a server, and wherein transmitting the executable code comprises transmitting the executable code to the server. 
     
     
       53. The electronic device of  claim 46 , wherein transmitting the executable code comprises transmitting the executable code to a second electronic device. 
     
     
       54. The electronic device of  claim 53 , wherein the second electronic device is connected to the electronic device over a local network. 
     
     
       55. The electronic device of  claim 46 , wherein transmitting the executable code comprises transmitting the executable code to a second electronic device;
 further comprising fulfilling the user request at the second electronic device. 
 
     
     
       56. The electronic device of  claim 46 , wherein the executable code enables a determination of whether information required for executing the at least one task is available to the virtual assistant.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to U.S. Provisional Patent Application Ser. No. 62/215,647, entitled “DISTRIBUTED PERSONAL ASSISTANT,” filed on Sep. 8, 2015. The content of this application is hereby incorporated by reference for all purposes. 
    
    
     FIELD 
     The present disclosure relates generally to a virtual assistant, and more specifically to executing tasks with a virtual assistant. 
     BACKGROUND 
     Intelligent automated assistants (or digital assistants) provide a beneficial interface between human users and electronic devices. Such assistants allow users to interact with devices or systems using natural language in spoken and/or text forms. For example, a user can access the services of an electronic device by providing a spoken user request to a digital assistant associated with the electronic device. The digital assistant can interpret the user&#39;s intent from the spoken user request and operationalize the user&#39;s intent into tasks. The tasks can then be performed by executing one or more services of the electronic device and a relevant output can be returned to the user in natural language form. 
     BRIEF SUMMARY 
     To the extent that tasks that are handled by a virtual assistant are performed at a server remote to the electronic device, the speed of task execution may become undesirably slow for a number of reasons. To the extent that tasks that are handled by a virtual assistant are performed at the electronic device itself, the speed of executing tasks also may become undesirably slow. 
     Accordingly, the present technique provides electronic devices with faster, more efficient methods for performing tasks with a digital assistant. Such methods and interfaces optionally complement or replace other methods for performing tasks with a digital assistant. Such methods and interfaces reduce the cognitive burden on a user and produce a more efficient human-machine interface. For battery-operated computing devices, such methods and interfaces may conserve power, increase the time between battery charges, and decrease the time required to perform tasks. 
     In some embodiments, a method of using a virtual assistant includes: at an electronic device configured to transmit and receive data, receiving a user request for a service from a virtual assistant; determining at least one task to perform in response to the user request; estimating at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimating, determining whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, causing the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generating executable code for carrying out the least one task; and transmitting the executable code from the electronic device. 
     In some embodiments, an electronic device includes a display; a memory; a microphone; a transmitter; a receiver; and a processor coupled to the display, the memory, the microphone, the transmitter and the receiver; the processor configured to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimate, determine whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generate executable code for carrying out the least one task; and transmit the executable code from the electronic device. 
     In some embodiments, a non-transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimate, determine whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generate executable code for carrying out the least one task; and transmit the executable code from the electronic device. 
     In some embodiments, a transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimate, determine whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generate executable code for carrying out the least one task; and transmit the executable code from the electronic device. 
     In some embodiments, a system utilizes an electronic device with a display, the system including: means for receiving a user request for a service from a virtual assistant; means for determining at least one task to perform in response to the user request; means for estimating at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimating, means for determining whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, means for causing the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: means for generating executable code for carrying out the least one task; and means for transmitting the executable code from the electronic device. 
     In some embodiments, an electronic device includes a processing unit that includes a transmitting unit, a receiving unit, a determining unit, an estimating unit, a causing unit, and a generating unit; the processing unit configured to: receive, using the receiving unit, a user request for a service from a virtual assistant; determine, using the determining unit, at least one task to perform in response to the user request; estimate, using the estimating unit, at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimate, determine, using the determining unit, whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, cause, using the causing unit, the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device: generate, using the generating unit, executable code for carrying out the least one task; and transmit, using the transmitting unit, the executable code from the electronic device. 
     In some embodiments, a method of using a virtual assistant distributed between a server and an electronic device includes: receiving a user request for a service from a virtual assistant; determining at least one task to perform in response to the user request; estimating at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimating, determining whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, causing the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server: generating executable code for carrying out the least one task; and transmitting the executable code from the server. 
     In some embodiments, an electronic device includes: a memory; a transmitter; a receiver; and a processor coupled to the memory, the transmitter and the receiver; the processor configured to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimating, determine whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server: generate executable code for carrying out the least one task; and transmit the executable code from the server. 
     In some embodiments, a non-transitory computer-readable storage medium stores one or more programs, the one or more programs comprising instructions, which when executed by an electronic device, cause the electronic device to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimating, determine whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server: generate executable code for carrying out the least one task; and transmit the executable code from the server. 
     In some embodiments, a transitory computer-readable storage medium stores one or more programs, the one or more programs comprising instructions, which when executed by an electronic device, cause the electronic device to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimating, determine whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server: generate executable code for carrying out the least one task; and transmit the executable code from the server. 
     In some embodiments, a system utilizes an electronic device with a display, the system including: means for receiving a user request for a service from a virtual assistant; means for determining at least one task to perform in response to the user request; means for estimating at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimating, means for determining whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, means for causing the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server: means for generating executable code for carrying out the least one task; and means for transmitting the executable code from the server. 
     In some embodiments, a server includes a processing unit including a receiving unit, a transmitting unit, a determining unit, an estimating unit, a generating unit. and a causing unit; the processing unit configured to: receive a user request for a service from a virtual assistant; determine at least one task to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimating, determine whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server: generate executable code for carrying out the least one task; and transmit the executable code from the server. 
     In some embodiments, a method of using a virtual assistant distributed between a server and a client includes receiving a user request for a service from a virtual assistant at an electronic device; determining a plurality of tasks to perform in response to the user request; estimating at least one performance characteristic for completion of the at least one task with the electronic device and with the server, based on at least one heuristic; based on the estimating, determining whether to execute the at least one task at one of the electronic device and the server; in accordance with a determination to execute the at least one task at the electronic device, causing the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the server, causing the execution of the at least one task at the server. 
     In some embodiments, an electronic device includes a display; a memory; and a processor coupled to the display and the memory; the processor configured to: receive a user request for a service from a virtual assistant at an electronic device; determine a plurality of tasks to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the electronic device and with the server, based on at least one heuristic; based on the estimate, determine whether to execute the at least one task at one of the electronic device and the server; in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server. 
     In some embodiments, a non-transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive a user request for a service from a virtual assistant; determine a plurality of tasks to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the electronic device and with the server, based on at least one heuristic; based on the estimate, determine whether to execute the at least one task at one of the electronic device and the server; in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server. 
     In some embodiments, a transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to: receive a user request for a service from a virtual assistant; determine a plurality of tasks to perform in response to the user request; estimate at least one performance characteristic for completion of the at least one task with the electronic device and with the server, based on at least one heuristic; based on the estimate, determine whether to execute the at least one task at one of the electronic device and the server; in accordance with a determination to execute the at least one task at the electronic device, cause the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the server, cause the execution of the at least one task at the server. 
     In some embodiments, a system utilizing an electronic device with a display includes: means for receiving a user request for a service from a virtual assistant at an electronic device; means for determining a plurality of tasks to perform in response to the user request; means for estimating at least one performance characteristic for completion of the at least one task with the electronic device and with the server, based on at least one heuristic; based on the estimating, means for determining whether to execute the at least one task at one of the electronic device and the server; in accordance with a determination to execute the at least one task at the electronic device, means for causing the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the server, means for causing the execution of the at least one task at the server. 
     In some embodiments, a first electronic device includes: a processing unit including a receiving unit, a determining unit, an estimating unit, and a causing unit; the processing unit configured to: receive, using the receiving unit, a user request for a service from a virtual assistant at the first electronic device; determine, using the determining unit, a plurality of tasks to perform in response to the user request; estimate, using the estimating unit, at least one performance characteristic for completion of the at least one task with the first electronic device and with a second electronic device, based on at least one heuristic; based on the estimate, determine, using the determining unit, whether to execute the at least one task at one of the first electronic device and the second electronic device; in accordance with a determination to execute the at least one task at the first electronic device, cause, using the causing unit, the execution of the at least one task at the first electronic device; in accordance with a determination to execute the at least one task at the second electronic device, cause, using the causing unit, the execution of the at least one task at the second electronic device. 
     Executable instructions for performing these functions are, optionally, included in a non-transitory computer-readable storage medium or other computer program product configured for execution by one or more processors. Executable instructions for performing these functions are, optionally, included in a transitory computer-readable storage medium or other computer program product configured for execution by one or more processors. 
     Thus, devices are provided with faster, more efficient methods and interfaces for task execution by a virtual assistant, thereby increasing the effectiveness, efficiency, and user satisfaction with such devices. Such methods and interfaces may complement or replace other methods for task execution by a virtual assistant. 
    
    
     
       DESCRIPTION OF THE FIGURES 
       For a better understanding of the various described embodiments, reference should be made to the Description of Embodiments below, in conjunction with the following drawings in which like reference numerals refer to corresponding parts throughout the figures. 
         FIG. 1  is a block diagram illustrating a system and environment for implementing a digital assistant according to various examples. 
         FIG. 2A  is a block diagram illustrating a portable multifunction device implementing the client-side portion of a digital assistant according to various examples. 
         FIG. 2B  is a block diagram illustrating exemplary components for event handling according to various examples. 
         FIG. 3  illustrates a portable multifunction device implementing the client-side portion of a digital assistant according to various examples. 
         FIG. 4  is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface according to various examples. 
         FIG. 5A  illustrates an exemplary user interface for a menu of applications on a portable multifunction device according to various examples. 
         FIG. 5B  illustrates an exemplary user interface for a multifunction device with a touch-sensitive surface that is separate from the display according to various examples. 
         FIG. 6A  illustrates a personal electronic device according to various examples. 
         FIG. 6B  is a block diagram illustrating a personal electronic device according to various examples. 
         FIG. 7A  is a block diagram illustrating a digital assistant system or a server portion thereof according to various examples. 
         FIG. 7B  illustrates the functions of the digital assistant shown in  FIG. 7A  according to various examples. 
         FIG. 7C  illustrates a portion of an ontology according to various examples. 
         FIGS. 8A-8D  illustrate exemplary user interfaces for a personal electronic device in accordance with some embodiments. 
         FIG. 8E  illustrates an exemplary virtual assistant including a client-side portion and a server-side portion. 
         FIGS. 9A-9B  illustrate a client-side process for executing tasks with a virtual assistant, according to various examples. 
         FIGS. 9C-9D  illustrate a server-side process for executing tasks with a virtual assistant, according to various examples. 
         FIGS. 9E-9H  illustrate a client-server process for executing tasks with a virtual assistant, according to various examples. 
         FIG. 10A  illustrates a functional block diagram of an electronic device according to various examples. 
         FIG. 10B  illustrates a functional block diagram of a server according to various examples. 
         FIG. 10C  illustrates a functional block diagram of an electronic device connected to a second electronic device, according to various examples. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     The following description sets forth exemplary methods, parameters, and the like. It should be recognized, however, that such description is not intended as a limitation on the scope of the present disclosure but is instead provided as a description of exemplary embodiments. 
     There is a need for electronic devices that provide efficient methods and interfaces for executing tasks with a virtual assistant. As described above, using known methods to execute tasks with a virtual assistant that includes a client-side component and a server-side component is not as effective as it might be, due to chronic or intermittent limitations associated with the client, the server, and/or the connection between them. Improved task execution with a virtual assistant can reduce the cognitive burden on a user, thereby enhancing productivity. Further, such techniques can reduce processor and battery power otherwise wasted on redundant user inputs. 
     Below,  FIGS. 1, 2A-2B, 3, 4, 5A-5B and 6A-6B  provide a description of exemplary devices for performing the techniques for discovering media based on a nonspecific, unstructured natural language request.  FIGS. 7A-7C  are block diagrams illustrating a digital assistant system or a server portion thereof, and a portion of an ontology associated with the digital assistant system.  FIG. 8A-8D  illustrate exemplary user interfaces for executing tasks with a virtual assistant.  FIG. 8E  illustrates an exemplary virtual assistant including a client-side portion and a server-side portion. The user interfaces in  FIGS. 8A-8D  and the virtual assistant of  FIG. 8E  are used to illustrate the processes described below, including the processes in  FIGS. 9A-9H .  FIGS. 9A-9H  are flow diagrams illustrating methods of executing tasks with a virtual assistant, in accordance with some embodiments. 
     Although the following description uses terms “first,” “second,” etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, a first touch could be termed a second touch, and, similarly, a second touch could be termed a first touch, without departing from the scope of the various described embodiments. The first touch and the second touch are both touches, but they are not the same touch. 
     The terminology used in the description of the various described embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used in the description of the various described embodiments and the appended claims, the singular forms “a”, “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. 
     The term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context. 
     Embodiments of electronic devices, user interfaces for such devices, and associated processes for using such devices are described. In some embodiments, the device is a portable communications device, such as a mobile telephone, that also contains other functions, such as PDA and/or music player functions. Exemplary embodiments of portable multifunction devices include, without limitation, the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif. Other portable electronic devices, such as laptops or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and/or touchpads), are, optionally, used. It should also be understood that, in some embodiments, the device is not a portable communications device, but is a desktop computer with a touch-sensitive surface (e.g., a touch screen display and/or a touchpad). 
     In the discussion that follows, an electronic device that includes a display and a touch-sensitive surface is described. It should be understood, however, that the electronic device optionally includes one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick. 
     The device may support a variety of applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk authoring application, a spreadsheet application, a gaming application, a telephone application, a video conferencing application, an e-mail application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital video camera application, a web browsing application, a digital music player application, and/or a digital video player application. 
     The various applications that are executed on the device optionally use at least one common physical user-interface device, such as the touch-sensitive surface. One or more functions of the touch-sensitive surface as well as corresponding information displayed on the device are, optionally, adjusted and/or varied from one application to the next and/or within a respective application. In this way, a common physical architecture (such as the touch-sensitive surface) of the device optionally supports the variety of applications with user interfaces that are intuitive and transparent to the user. 
       FIG. 1  illustrates a block diagram of system  100  according to various examples. In some examples, system  100  can implement a digital assistant. The terms “digital assistant,” “virtual assistant,” “intelligent automated assistant,” or “automatic digital assistant” can refer to any information processing system that interprets natural language input in spoken and/or textual form to infer user intent, and performs actions based on the inferred user intent. For example, to act on an inferred user intent, the system can perform one or more of the following: identifying a task flow with steps and parameters designed to accomplish the inferred user intent, inputting specific requirements from the inferred user intent into the task flow; executing the task flow by invoking programs, methods, services, APIs, or the like; and generating output responses to the user in an audible (e.g., speech) and/or visual form. 
     Specifically, a digital assistant can be capable of accepting a user request at least partially in the form of a natural language command, request, statement, narrative, and/or inquiry. Typically, the user request can seek either an informational answer or performance of a task by the digital assistant. A satisfactory response to the user request can be a provision of the requested informational answer, a performance of the requested task, or a combination of the two. For example, a user can ask the digital assistant a question, such as “Where am I right now?” Based on the user&#39;s current location, the digital assistant can answer, “You are in Central Park near the west gate.” The user can also request the performance of a task, for example, “Please invite my friends to my girlfriend&#39;s birthday party next week.” In response, the digital assistant can acknowledge the request by saying “Yes, right away,” and then send a suitable calendar invite on behalf of the user to each of the user&#39;s friends listed in the user&#39;s electronic address book. During performance of a requested task, the digital assistant can sometimes interact with the user in a continuous dialogue involving multiple exchanges of information over an extended period of time. There are numerous other ways of interacting with a digital assistant to request information or performance of various tasks. In addition to providing verbal responses and taking programmed actions, the digital assistant can also provide responses in other visual or audio forms, e.g., as text, alerts, music, videos, animations, etc. 
     As shown in  FIG. 1 , in some examples, a digital assistant can be implemented according to a client-server model. The digital assistant can include client-side portion  102  (hereafter “DA client  102 ”) executed on user device  104  and server-side portion  106  (hereafter “DA server  106 ”) executed on server system  108 . DA client  102  can communicate with DA server  106  through one or more networks  110 . DA client  102  can provide client-side functionalities such as user-facing input and output processing and communication with DA server  106 . DA server  106  can provide server-side functionalities for any number of DA clients  102  each residing on a respective user device  104 . 
     In some examples, DA server  106  can include client-facing I/O interface  112 , one or more processing modules  114 , data and models  116 , and I/O interface to external services  118 . The client-facing I/O interface  112  can facilitate the client-facing input and output processing for DA server  106 . One or more processing modules  114  can utilize data and models  116  to process speech input and determine the user&#39;s intent based on natural language input. Further, one or more processing modules  114  perform task execution based on inferred user intent. In some examples, DA server  106  can communicate with external services  120  through network(s)  110  for task completion or information acquisition. I/O interface to external services  118  can facilitate such communications. 
     User device  104  can be any suitable electronic device. For example, user devices can be a portable multifunctional device (e.g., device  200 , described below with reference to  FIG. 2A ), a multifunctional device (e.g., device  400 , described below with reference to  FIG. 4 ), or a personal electronic device (e.g., device  600 , described below with reference to  FIG. 6A-B .) A portable multifunctional device can be, for example, a mobile telephone that also contains other functions, such as PDA and/or music player functions. Specific examples of portable multifunction devices can include the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif. Other examples of portable multifunction devices can include, without limitation, laptop or tablet computers. Further, in some examples, user device  104  can be a non-portable multifunctional device. In particular, user device  104  can be a desktop computer, a game console, a television, or a television set-top box. In some examples, user device  104  can include a touch-sensitive surface (e.g., touch screen displays and/or touchpads). Further, user device  104  can optionally include one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick. Various examples of electronic devices, such as multifunctional devices, are described below in greater detail. 
     Examples of communication network(s)  110  can include local area networks (LAN) and wide area networks (WAN), e.g., the Internet. Communication network(s)  110  can be implemented using any known network protocol, including various wired or wireless protocols, such as, for example, Ethernet, Universal Serial Bus (USB), FIREWIRE, Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wi-Fi, voice over Internet Protocol (VoIP), Wi-MAX, or any other suitable communication protocol. 
     Server system  108  can be implemented on one or more standalone data processing apparatus or a distributed network of computers. In some examples, server system  108  can also employ various virtual devices and/or services of third-party service providers (e.g., third-party cloud service providers) to provide the underlying computing resources and/or infrastructure resources of server system  108 . 
     In some examples, user device  104  can communicate with DA server  106  via second user device  122 . Second user device  122  can be similar or identical to user device  104 . For example, second user device  122  can be similar to devices  200 ,  400 , or  600  described below with reference to  FIGS. 2A, 4, and 6A -B. User device  104  can be configured to communicatively couple to second user device  122  via a direct communication connection, such as Bluetooth, NFC, BTLE, or the like, or via a wired or wireless network, such as a local Wi-Fi network. In some examples, second user device  122  can be configured to act as a proxy between user device  104  and DA server  106 . For example, DA client  102  of user device  104  can be configured to transmit information (e.g., a user request received at user device  104 ) to DA server  106  via second user device  122 . DA server  106  can process the information and return relevant data (e.g., data content responsive to the user request) to user device  104  via second user device  122 . 
     In some examples, user device  104  can be configured to communicate abbreviated requests for data to second user device  122  to reduce the amount of information transmitted from user device  104 . Second user device  122  can be configured to determine supplemental information to add to the abbreviated request to generate a complete request to transmit to DA server  106 . This system architecture can advantageously allow user device  104  having limited communication capabilities and/or limited battery power (e.g., a watch or a similar compact electronic device) to access services provided by DA server  106  by using second user device  122 , having greater communication capabilities and/or battery power (e.g., a mobile phone, laptop computer, tablet computer, or the like), as a proxy to DA server  106 . While only two user devices  104  and  122  are shown in  FIG. 1 , it should be appreciated that system  100  can include any number and type of user devices configured in this proxy configuration to communicate with DA server system  106 . 
     Although the digital assistant shown in  FIG. 1  can include both a client-side portion (e.g., DA client  102 ) and a server-side portion (e.g., DA server  106 ), in some examples, the functions of a digital assistant can be implemented as a standalone application installed on a user device. In addition, the divisions of functionalities between the client and server portions of the digital assistant can vary in different implementations. For instance, in some examples, the DA client can be a thin-client that provides only user-facing input and output processing functions, and delegates all other functionalities of the digital assistant to a backend server. 
     1. Electronic Devices 
     Attention is now directed toward embodiments of electronic devices for implementing the client-side portion of a digital assistant.  FIG. 2A  is a block diagram illustrating portable multifunction device  200  with touch-sensitive display system  212  in accordance with some embodiments. Touch-sensitive display  212  is sometimes called a “touch screen” for convenience and is sometimes known as or called a “touch-sensitive display system.” Device  200  includes memory  202  (which optionally includes one or more computer-readable storage mediums), memory controller  222 , one or more processing units (CPUs)  220 , peripherals interface  218 , RF circuitry  208 , audio circuitry  210 , speaker  211 , microphone  213 , input/output (I/O) subsystem  206 , other input control devices  216 , and external port  224 . Device  200  optionally includes one or more optical sensors  264 . Device  200  optionally includes one or more contact intensity sensors  265  for detecting intensity of contacts on device  200  (e.g., a touch-sensitive surface such as touch-sensitive display system  212  of device  200 ). Device  200  optionally includes one or more tactile output generators  267  for generating tactile outputs on device  200  (e.g., generating tactile outputs on a touch-sensitive surface such as touch-sensitive display system  212  of device  200  or touchpad  455  of device  400 ). These components optionally communicate over one or more communication buses or signal lines  203 . 
     As used in the specification and claims, the term “intensity” of a contact on a touch-sensitive surface refers to the force or pressure (force per unit area) of a contact (e.g., a finger contact) on the touch-sensitive surface, or to a substitute (proxy) for the force or pressure of a contact on the touch-sensitive surface. The intensity of a contact has a range of values that includes at least four distinct values and more typically includes hundreds of distinct values (e.g., at least 256). Intensity of a contact is, optionally, determined (or measured) using various approaches and various sensors or combinations of sensors. For example, one or more force sensors underneath or adjacent to the touch-sensitive surface are, optionally, used to measure force at various points on the touch-sensitive surface. In some implementations, force measurements from multiple force sensors are combined (e.g., a weighted average) to determine an estimated force of a contact. Similarly, a pressure-sensitive tip of a stylus is, optionally, used to determine a pressure of the stylus on the touch-sensitive surface. Alternatively, the size of the contact area detected on the touch-sensitive surface and/or changes thereto, the capacitance of the touch-sensitive surface proximate to the contact and/or changes thereto, and/or the resistance of the touch-sensitive surface proximate to the contact and/or changes thereto are, optionally, used as a substitute for the force or pressure of the contact on the touch-sensitive surface. In some implementations, the substitute measurements for contact force or pressure are used directly to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is described in units corresponding to the substitute measurements). In some implementations, the substitute measurements for contact force or pressure are converted to an estimated force or pressure, and the estimated force or pressure is used to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is a pressure threshold measured in units of pressure). Using the intensity of a contact as an attribute of a user input allows for user access to additional device functionality that may otherwise not be accessible by the user on a reduced-size device with limited real estate for displaying affordances (e.g., on a touch-sensitive display) and/or receiving user input (e.g., via a touch-sensitive display, a touch-sensitive surface, or a physical/mechanical control such as a knob or a button). 
     As used in the specification and claims, the term “tactile output” refers to physical displacement of a device relative to a previous position of the device, physical displacement of a component (e.g., a touch-sensitive surface) of a device relative to another component (e.g., housing) of the device, or displacement of the component relative to a center of mass of the device that will be detected by a user with the user&#39;s sense of touch. For example, in situations where the device or the component of the device is in contact with a surface of a user that is sensitive to touch (e.g., a finger, palm, or other part of a user&#39;s hand), the tactile output generated by the physical displacement will be interpreted by the user as a tactile sensation corresponding to a perceived change in physical characteristics of the device or the component of the device. For example, movement of a touch-sensitive surface (e.g., a touch-sensitive display or trackpad) is, optionally, interpreted by the user as a “down click” or “up click” of a physical actuator button. In some cases, a user will feel a tactile sensation such as an “down click” or “up click” even when there is no movement of a physical actuator button associated with the touch-sensitive surface that is physically pressed (e.g., displaced) by the user&#39;s movements. As another example, movement of the touch-sensitive surface is, optionally, interpreted or sensed by the user as “roughness” of the touch-sensitive surface, even when there is no change in smoothness of the touch-sensitive surface. While such interpretations of touch by a user will be subject to the individualized sensory perceptions of the user, there are many sensory perceptions of touch that are common to a large majority of users. Thus, when a tactile output is described as corresponding to a particular sensory perception of a user (e.g., an “up click,” a “down click,” “roughness”), unless otherwise stated, the generated tactile output corresponds to physical displacement of the device or a component thereof that will generate the described sensory perception for a typical (or average) user. 
     It should be appreciated that device  200  is only one example of a portable multifunction device, and that device  200  optionally has more or fewer components than shown, optionally combines two or more components, or optionally has a different configuration or arrangement of the components. The various components shown in  FIG. 2A  are implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application-specific integrated circuits. 
     Memory  202  may include one or more computer-readable storage mediums. The computer-readable storage mediums may be tangible and non-transitory. Memory  202  may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices. Memory controller  222  may control access to memory  202  by other components of device  200 . 
     In some examples, a non-transitory computer-readable storage medium of memory  202  can be used to store instructions (e.g., for performing aspects of method  900 , described below) for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In other examples, the instructions (e.g., for performing aspects of method  900 , described below) can be stored on a non-transitory computer-readable storage medium (not shown) of the server system  108  or can be divided between the non-transitory computer-readable storage medium of memory  202  and the non-transitory computer-readable storage medium of server system  108 . In the context of this document, a “non-transitory computer-readable storage medium” can be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device. 
     Peripherals interface  218  can be used to couple input and output peripherals of the device to CPU  220  and memory  202 . The one or more processors  220  run or execute various software programs and/or sets of instructions stored in memory  202  to perform various functions for device  200  and to process data. In some embodiments, peripherals interface  218 , CPU  220 , and memory controller  222  may be implemented on a single chip, such as chip  204 . In some other embodiments, they may be implemented on separate chips. 
     RF (radio frequency) circuitry  208  receives and sends RF signals, also called electromagnetic signals. RF circuitry  208  converts electrical signals to/from electromagnetic signals and communicates with communications networks and other communications devices via the electromagnetic signals. RF circuitry  208  optionally includes well-known circuitry for performing these functions, including but not limited to an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC chipset, a subscriber identity module (SIM) card, memory, and so forth. RF circuitry  208  optionally communicates with networks, such as the Internet, also referred to as the World Wide Web (WWW), an intranet and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN) and/or a metropolitan area network (MAN), and other devices by wireless communication. The RF circuitry  208  optionally includes well-known circuitry for detecting near field communication (NFC) fields, such as by a short-range communication radio. The wireless communication optionally uses any of a plurality of communications standards, protocols, and technologies, including but not limited to Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), high-speed downlink packet access (HSDPA), high-speed uplink packet access (HSUPA), Evolution, Data-Only (EV-DO), HSPA, HSPA+, Dual-Cell HSPA (DC-HSPDA), long term evolution (LTE), near field communication (NFC), wideband code division multiple access (W-CDMA), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Bluetooth Low Energy (BTLE), Wireless Fidelity (Wi-Fi) (e.g., IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, IEEE 802.11n, and/or IEEE 802.11ac), voice over Internet Protocol (VoIP), Wi-MAX, a protocol for e mail (e.g., Internet message access protocol (IMAP) and/or post office protocol (POP)), instant messaging (e.g., extensible messaging and presence protocol (XMPP), Session Initiation Protocol for Instant Messaging and Presence Leveraging Extensions (SIMPLE), Instant Messaging and Presence Service (IMPS)), and/or Short Message Service (SMS), or any other suitable communication protocol, including communication protocols not yet developed as of the filing date of this document. 
     Audio circuitry  210 , speaker  211 , and microphone  213  provide an audio interface between a user and device  200 . Audio circuitry  210  receives audio data from peripherals interface  218 , converts the audio data to an electrical signal, and transmits the electrical signal to speaker  211 . Speaker  211  converts the electrical signal to human-audible sound waves. Audio circuitry  210  also receives electrical signals converted by microphone  213  from sound waves. Audio circuitry  210  converts the electrical signal to audio data and transmits the audio data to peripherals interface  218  for processing. Audio data may be retrieved from and/or transmitted to memory  202  and/or RF circuitry  208  by peripherals interface  218 . In some embodiments, audio circuitry  210  also includes a headset jack (e.g.,  312 ,  FIG. 3 ). The headset jack provides an interface between audio circuitry  210  and removable audio input/output peripherals, such as output-only headphones or a headset with both output (e.g., a headphone for one or both ears) and input (e.g., a microphone). 
     I/O subsystem  206  couples input/output peripherals on device  200 , such as touch screen  212  and other input control devices  216 , to peripherals interface  218 . I/O subsystem  206  optionally includes display controller  256 , optical sensor controller  258 , intensity sensor controller  259 , haptic feedback controller  261 , and one or more input controllers  260  for other input or control devices. The one or more input controllers  260  receive/send electrical signals from/to other input control devices  216 . The other input control devices  216  optionally include physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth. In some alternate embodiments, input controller(s)  260  are, optionally, coupled to any (or none) of the following: a keyboard, an infrared port, a USB port, and a pointer device such as a mouse. The one or more buttons (e.g.,  308 ,  FIG. 3 ) optionally include an up/down button for volume control of speaker  211  and/or microphone  213 . The one or more buttons optionally include a push button (e.g.,  306 ,  FIG. 3 ). 
     A quick press of the push button may disengage a lock of touch screen  212  or begin a process that uses gestures on the touch screen to unlock the device, as described in U.S. patent application Ser. No. 11/322,549, “Unlocking a Device by Performing Gestures on an Unlock Image,” filed Dec. 23, 2005, U.S. Pat. No. 7,657,849, which is hereby incorporated by reference in its entirety. A longer press of the push button (e.g.,  306 ) may turn power to device  200  on or off. The user may be able to customize a functionality of one or more of the buttons. Touch screen  212  is used to implement virtual or soft buttons and one or more soft keyboards. 
     Touch-sensitive display  212  provides an input interface and an output interface between the device and a user. Display controller  256  receives and/or sends electrical signals from/to touch screen  212 . Touch screen  212  displays visual output to the user. The visual output may include graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output may correspond to user-interface objects. 
     Touch screen  212  has a touch-sensitive surface, sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact. Touch screen  212  and display controller  256  (along with any associated modules and/or sets of instructions in memory  202 ) detect contact (and any movement or breaking of the contact) on touch screen  212  and convert the detected contact into interaction with user-interface objects (e.g., one or more soft keys, icons, web pages, or images) that are displayed on touch screen  212 . In an exemplary embodiment, a point of contact between touch screen  212  and the user corresponds to a finger of the user. 
     Touch screen  212  may use LCD (liquid crystal display) technology, LPD (light emitting polymer display) technology, or LED (light emitting diode) technology, although other display technologies may be used in other embodiments. Touch screen  212  and display controller  256  may detect contact and any movement or breaking thereof using any of a plurality of touch sensing technologies now known or later developed, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch screen  212 . In an exemplary embodiment, projected mutual capacitance sensing technology is used, such as that found in the iPhone® and iPod Touch® from Apple Inc. of Cupertino, Calif. 
     A touch-sensitive display in some embodiments of touch screen  212  may be analogous to the multi-touch sensitive touchpads described in the following U.S. Pat. No. 6,323,846 (Westerman et al.), U.S. Pat. No. 6,570,557 (Westerman et al.), and/or U.S. Pat. No. 6,677,932 (Westerman), and/or U.S. Patent Publication 2002/0015024A1, each of which is hereby incorporated by reference in its entirety. However, touch screen  212  displays visual output from device  200 , whereas touch-sensitive touchpads do not provide visual output. 
     A touch-sensitive display in some embodiments of touch screen  212  may be as described in the following applications: (1) U.S. patent application Ser. No. 11/381,313, “Multipoint Touch Surface Controller,” filed May 2, 2006; (2) U.S. patent application Ser. No. 10/840,862, “Multipoint Touchscreen,” filed May 6, 2004; (3) U.S. patent application Ser. No. 10/903,964, “Gestures For Touch Sensitive Input Devices,” filed Jul. 30, 2004; (4) U.S. patent application Ser. No. 11/048,264, “Gestures For Touch Sensitive Input Devices,” filed Jan. 31, 2005; (5) U.S. patent application Ser. No. 11/038,590, “Mode-Based Graphical User Interfaces For Touch Sensitive Input Devices,” filed Jan. 18, 2005; (6) U.S. patent application Ser. No. 11/228,758, “Virtual Input Device Placement On A Touch Screen User Interface,” filed Sep. 16, 2005; (7) U.S. patent application Ser. No. 11/228,700, “Operation Of A Computer With A Touch Screen Interface,” filed Sep. 16, 2005; (8) U.S. patent application Ser. No. 11/228,737, “Activating Virtual Keys Of A Touch-Screen Virtual Keyboard,” filed Sep. 16, 2005; and (9) U.S. patent application Ser. No. 11/367,749, “Multi-Functional Hand-Held Device,” filed Mar. 3, 2006. All of these applications are incorporated by reference herein in their entirety. 
     Touch screen  212  may have a video resolution in excess of 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi. The user may make contact with touch screen  212  using any suitable object or appendage, such as a stylus, a finger, and so forth. In some embodiments, the user interface is designed to work primarily with finger-based contacts and gestures, which can be less precise than stylus-based input due to the larger area of contact of a finger on the touch screen. In some embodiments, the device translates the rough finger-based input into a precise pointer/cursor position or command for performing the actions desired by the user. 
     In some embodiments, in addition to the touch screen, device  200  may include a touchpad (not shown) for activating or deactivating particular functions. In some embodiments, the touchpad is a touch-sensitive area of the device that, unlike the touch screen, does not display visual output. The touchpad may be a touch-sensitive surface that is separate from touch screen  212  or an extension of the touch-sensitive surface formed by the touch screen. 
     Device  200  also includes power system  262  for powering the various components. Power system  262  may include a power management system, one or more power sources (e.g., battery, alternating current (AC)), a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator (e.g., a light-emitting diode (LED)) and any other components associated with the generation, management and distribution of power in portable devices. 
     Device  200  may also include one or more optical sensors  264 .  FIG. 2A  shows an optical sensor coupled to optical sensor controller  258  in I/O subsystem  206 . Optical sensor  264  may include charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) phototransistors. Optical sensor  264  receives light from the environment, projected through one or more lenses, and converts the light to data representing an image. In conjunction with imaging module  243  (also called a camera module), optical sensor  264  may capture still images or video. In some embodiments, an optical sensor is located on the back of device  200 , opposite touch screen display  212  on the front of the device so that the touch screen display may be used as a viewfinder for still and/or video image acquisition. In some embodiments, an optical sensor is located on the front of the device so that the user&#39;s image may be obtained for video conferencing while the user views the other video conference participants on the touch screen display. In some embodiments, the position of optical sensor  264  can be changed by the user (e.g., by rotating the lens and the sensor in the device housing) so that a single optical sensor  264  may be used along with the touch screen display for both video conferencing and still and/or video image acquisition. 
     Device  200  optionally also includes one or more contact intensity sensors  265 .  FIG. 2A  shows a contact intensity sensor coupled to intensity sensor controller  259  in I/O subsystem  206 . Contact intensity sensor  265  optionally includes one or more piezoresistive strain gauges, capacitive force sensors, electric force sensors, piezoelectric force sensors, optical force sensors, capacitive touch-sensitive surfaces, or other intensity sensors (e.g., sensors used to measure the force (or pressure) of a contact on a touch-sensitive surface). Contact intensity sensor  265  receives contact intensity information (e.g., pressure information or a proxy for pressure information) from the environment. In some embodiments, at least one contact intensity sensor is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system  212 ). In some embodiments, at least one contact intensity sensor is located on the back of device  200 , opposite touch screen display  212 , which is located on the front of device  200 . 
     Device  200  may also include one or more proximity sensors  266 .  FIG. 2A  shows proximity sensor  266  coupled to peripherals interface  218 . Alternately, proximity sensor  266  may be coupled to input controller  260  in I/O subsystem  206 . Proximity sensor  266  may perform as described in U.S. patent application Ser. No. 11/241,839, “Proximity Detector In Handheld Device”; Ser. No. 11/240,788, “Proximity Detector In Handheld Device”; Ser. No. 11/620,702, “Using Ambient Light Sensor To Augment Proximity Sensor Output”; Ser. No. 11/586,862, “Automated Response To And Sensing Of User Activity In Portable Devices”; and Ser. No. 11/638,251, “Methods And Systems For Automatic Configuration Of Peripherals,” which are hereby incorporated by reference in their entirety. In some embodiments, the proximity sensor turns off and disables touch screen  212  when the multifunction device is placed near the user&#39;s ear (e.g., when the user is making a phone call). 
     Device  200  optionally also includes one or more tactile output generators  267 .  FIG. 2A  shows a tactile output generator coupled to haptic feedback controller  261  in I/O subsystem  206 . Tactile output generator  267  optionally includes one or more electroacoustic devices such as speakers or other audio components and/or electromechanical devices that convert energy into linear motion such as a motor, solenoid, electroactive polymer, piezoelectric actuator, electrostatic actuator, or other tactile output generating component (e.g., a component that converts electrical signals into tactile outputs on the device). Contact intensity sensor  265  receives tactile feedback generation instructions from haptic feedback module  233  and generates tactile outputs on device  200  that are capable of being sensed by a user of device  200 . In some embodiments, at least one tactile output generator is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system  212 ) and, optionally, generates a tactile output by moving the touch-sensitive surface vertically (e.g., in/out of a surface of device  200 ) or laterally (e.g., back and forth in the same plane as a surface of device  200 ). In some embodiments, at least one tactile output generator sensor is located on the back of device  200 , opposite touch screen display  212 , which is located on the front of device  200 . 
     Device  200  may also include one or more accelerometers  268 .  FIG. 2A  shows accelerometer  268  coupled to peripherals interface  218 . Alternately, accelerometer  268  may be coupled to an input controller  260  in I/O subsystem  206 . Accelerometer  268  may perform as described in U.S. Patent Publication No. 20050190059, “Acceleration-based Theft Detection System for Portable Electronic Devices,” and U.S. Patent Publication No. 20060017692, “Methods And Apparatuses For Operating A Portable Device Based On An Accelerometer,” both of which are incorporated by reference herein in their entirety. In some embodiments, information is displayed on the touch screen display in a portrait view or a landscape view based on an analysis of data received from the one or more accelerometers. Device  200  optionally includes, in addition to accelerometer(s)  268 , a magnetometer (not shown) and a GPS (or GLONASS or other global navigation system) receiver (not shown) for obtaining information concerning the location and orientation (e.g., portrait or landscape) of device  200 . 
     In some embodiments, the software components stored in memory  202  include operating system  226 , communication module (or set of instructions)  228 , contact/motion module (or set of instructions)  230 , graphics module (or set of instructions)  232 , text input module (or set of instructions)  234 , Global Positioning System (GPS) module (or set of instructions)  235 , Digital Assistant Client Module  229 , and applications (or sets of instructions)  236 . Further, memory  202  can store data and models, such as user data and models  231 . Furthermore, in some embodiments, memory  202  ( FIG. 2A ) or  470  ( FIG. 4 ) stores device/global internal state  257 , as shown in  FIGS. 2A and 4 . Device/global internal state  257  includes one or more of: active application state, indicating which applications, if any, are currently active; display state, indicating what applications, views or other information occupy various regions of touch screen display  212 ; sensor state, including information obtained from the device&#39;s various sensors and input control devices  216 ; and location information concerning the device&#39;s location and/or attitude. 
     Operating system  226  (e.g., Darwin, RTXC, LINUX, UNIX, OS X, iOS, WINDOWS, or an embedded operating system such as VxWorks) includes various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communication between various hardware and software components. 
     Communication module  228  facilitates communication with other devices over one or more external ports  224  and also includes various software components for handling data received by RF circuitry  208  and/or external port  224 . External port  224  (e.g., Universal Serial Bus (USB), FIREWIRE, etc.) is adapted for coupling directly to other devices or indirectly over a network (e.g., the Internet, wireless LAN, etc.). In some embodiments, the external port is a multi-pin (e.g., 30-pin) connector that is the same as, or similar to and/or compatible with, the 30-pin connector used on iPod® (trademark of Apple Inc.) devices. 
     Contact/motion module  230  optionally detects contact with touch screen  212  (in conjunction with display controller  256 ) and other touch-sensitive devices (e.g., a touchpad or physical click wheel). Contact/motion module  230  includes various software components for performing various operations related to detection of contact, such as determining if contact has occurred (e.g., detecting a finger-down event), determining an intensity of the contact (e.g., the force or pressure of the contact or a substitute for the force or pressure of the contact), determining if there is movement of the contact and tracking the movement across the touch-sensitive surface (e.g., detecting one or more finger-dragging events), and determining if the contact has ceased (e.g., detecting a finger-up event or a break in contact). Contact/motion module  230  receives contact data from the touch-sensitive surface. Determining movement of the point of contact, which is represented by a series of contact data, optionally includes determining speed (magnitude), velocity (magnitude and direction), and/or an acceleration (a change in magnitude and/or direction) of the point of contact. These operations are, optionally, applied to single contacts (e.g., one finger contacts) or to multiple simultaneous contacts (e.g., “multitouch”/multiple finger contacts). In some embodiments, contact/motion module  230  and display controller  256  detect contact on a touchpad. 
     In some embodiments, contact/motion module  230  uses a set of one or more intensity thresholds to determine whether an operation has been performed by a user (e.g., to determine whether a user has “clicked” on an icon). In some embodiments, at least a subset of the intensity thresholds are determined in accordance with software parameters (e.g., the intensity thresholds are not determined by the activation thresholds of particular physical actuators and can be adjusted without changing the physical hardware of device  200 ). For example, a mouse “click” threshold of a trackpad or touch screen display can be set to any of a large range of predefined threshold values without changing the trackpad or touch screen display hardware. Additionally, in some implementations, a user of the device is provided with software settings for adjusting one or more of the set of intensity thresholds (e.g., by adjusting individual intensity thresholds and/or by adjusting a plurality of intensity thresholds at once with a system-level click “intensity” parameter). 
     Contact/motion module  230  optionally detects a gesture input by a user. Different gestures on the touch-sensitive surface have different contact patterns (e.g., different motions, timings, and/or intensities of detected contacts). Thus, a gesture is, optionally, detected by detecting a particular contact pattern. For example, detecting a finger tap gesture includes detecting a finger-down event followed by detecting a finger-up (liftoff) event at the same position (or substantially the same position) as the finger-down event (e.g., at the position of an icon). As another example, detecting a finger swipe gesture on the touch-sensitive surface includes detecting a finger-down event followed by detecting one or more finger-dragging events, and subsequently followed by detecting a finger-up (liftoff) event. 
     Graphics module  232  includes various known software components for rendering and displaying graphics on touch screen  212  or other display, including components for changing the visual impact (e.g., brightness, transparency, saturation, contrast, or other visual property) of graphics that are displayed. As used herein, the term “graphics” includes any object that can be displayed to a user, including, without limitation, text, web pages, icons (such as user-interface objects including soft keys), digital images, videos, animations, and the like. 
     In some embodiments, graphics module  232  stores data representing graphics to be used. Each graphic is, optionally, assigned a corresponding code. Graphics module  232  receives, from applications etc., one or more codes specifying graphics to be displayed along with, if necessary, coordinate data and other graphic property data, and then generates screen image data to output to display controller  256 . 
     Haptic feedback module  233  includes various software components for generating instructions used by tactile output generator(s)  267  to produce tactile outputs at one or more locations on device  200  in response to user interactions with device  200 . 
     Text input module  234 , which may be a component of graphics module  232 , provides soft keyboards for entering text in various applications (e.g., contacts  237 , e mail  240 , IM  241 , browser  247 , and any other application that needs text input). 
     GPS module  235  determines the location of the device and provides this information for use in various applications (e.g., to telephone  238  for use in location-based dialing; to camera  243  as picture/video metadata; and to applications that provide location-based services such as weather widgets, local yellow page widgets, and map/navigation widgets). 
     Digital assistant client module  229  can include various client-side digital assistant instructions to provide the client-side functionalities of the digital assistant. For example, digital assistant client module  229  can be capable of accepting voice input (e.g., speech input), text input, touch input, and/or gestural input through various user interfaces (e.g., microphone  213 , accelerometer(s)  268 , touch-sensitive display system  212 , optical sensor(s)  229 , other input control devices  216 , etc.) of portable multifunction device  200 . Digital assistant client module  229  can also be capable of providing output in audio (e.g., speech output), visual, and/or tactile forms through various output interfaces (e.g., speaker  211 , touch-sensitive display system  212 , tactile output generator(s)  267 , etc.) of portable multifunction device  200 . For example, output can be provided as voice, sound, alerts, text messages, menus, graphics, videos, animations, vibrations, and/or combinations of two or more of the above. During operation, digital assistant client module  229  can communicate with DA server  106  using RF circuitry  208 . The terms “digital assistant,” “virtual assistant” and “personal assistant” are used as synonyms in this document such that all have the same meaning. 
     User data and models  231  can include various data associated with the user (e.g., user-specific vocabulary data, user preference data, user-specified name pronunciations, data from the user&#39;s electronic address book, to-do lists, shopping lists, etc.) to provide the client-side functionalities of the digital assistant. Further, user data and models  231  can includes various models (e.g., speech recognition models, statistical language models, natural language processing models, ontology, task flow models, service models, etc.) for processing user input and determining user intent. 
     In some examples, digital assistant client module  229  can utilize the various sensors, subsystems, and peripheral devices of portable multifunction device  200  to gather additional information from the surrounding environment of the portable multifunction device  200  to establish a context associated with a user, the current user interaction, and/or the current user input. In some examples, digital assistant client module  229  can provide the contextual information or a subset thereof with the user input to DA server  106  to help infer the user&#39;s intent. In some examples, the digital assistant can also use the contextual information to determine how to prepare and deliver outputs to the user. Contextual information can be referred to as context data. 
     In some examples, the contextual information that accompanies the user input can include sensor information, e.g., lighting, ambient noise, ambient temperature, images or videos of the surrounding environment, etc. In some examples, the contextual information can also include the physical state of the device, e.g., device orientation, device location, device temperature, power level, speed, acceleration, motion patterns, cellular signals strength, etc. In some examples, information related to the software state of DA server  106 , e.g., running processes, installed programs, past and present network activities, background services, error logs, resources usage, etc., and of portable multifunction device  200  can be provided to DA server  106  as contextual information associated with a user input. 
     In some examples, the digital assistant client module  229  can selectively provide information (e.g., user data  231 ) stored on the portable multifunction device  200  in response to requests from DA server  106 . In some examples, digital assistant client module  229  can also elicit additional input from the user via a natural language dialogue or other user interfaces upon request by DA server  106 . Digital assistant client module  229  can pass the additional input to DA server  106  to help DA server  106  in intent deduction and/or fulfillment of the user&#39;s intent expressed in the user request. 
     A more detailed description of a digital assistant is described below with reference to  FIGS. 7A-C . It should be recognized that digital assistant client module  229  can include any number of the sub-modules of digital assistant module  726  described below. 
     Applications  236  may include the following modules (or sets of instructions), or a subset or superset thereof:
         Contacts module  237  (sometimes called an address book or contact list);   Telephone module  238 ;   Video conference module  239 ;   E-mail client module  240 ;   Instant messaging (IM) module  241 ;   Workout support module  242 ;   Camera module  243  for still and/or video images;   Image management module  244 ;   Video player module;   Music player module;   Browser module  247 ;   Calendar module  248 ;   Widget modules  249 , which may include one or more of: weather widget  249 - 1 , stocks widget  249 - 2 , calculator widget  249 - 3 , alarm clock widget  249 - 4 , dictionary widget  249 - 5 , and other widgets obtained by the user, as well as user-created widgets  249 - 6 ;   Widget creator module  250  for making user-created widgets  249 - 6 ;   Search module  251 ;   Video and music player module  252 , which merges video player module and music player module;   Notes module  253 ;   Map module  254 ; and/or   Online video module  255 .       

     Examples of other applications  236  that may be stored in memory  202  include other word processing applications, other image editing applications, drawing applications, presentation applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice replication. 
     In conjunction with touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , contacts module  237  may be used to manage an address book or contact list (e.g., stored in application internal state  292  of contacts module  237  in memory  202  or memory  470 ), including: adding name(s) to the address book; deleting name(s) from the address book; associating telephone number(s), e-mail address(es), physical address(es) or other information with a name; associating an image with a name; categorizing and sorting names; providing telephone numbers or e-mail addresses to initiate and/or facilitate communications by telephone  238 , video conference module  239 , e-mail  240 , or IM  241 ; and so forth. 
     In conjunction with RF circuitry  208 , audio circuitry  210 , speaker  211 , microphone  213 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , telephone module  238  may be used to enter a sequence of characters corresponding to a telephone number, access one or more telephone numbers in contacts module  237 , modify a telephone number that has been entered, dial a respective telephone number, conduct a conversation, and disconnect or hang up when the conversation is completed. As noted above, the wireless communication may use any of a plurality of communications standards, protocols, and technologies. 
     In conjunction with RF circuitry  208 , audio circuitry  210 , speaker  211 , microphone  213 , touch screen  212 , display controller  256 , optical sensor  264 , optical sensor controller  258 , contact/motion module  230 , graphics module  232 , text input module  234 , contacts module  237 , and telephone module  238 , video conference module  239  includes executable instructions to initiate, conduct, and terminate a video conference between a user and one or more other participants in accordance with user instructions. 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , e-mail client module  240  includes executable instructions to create, send, receive, and manage e-mail in response to user instructions. In conjunction with image management module  244 , e-mail client module  240  makes it very easy to create and send e-mails with still or video images taken with camera module  243 . 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , the instant messaging module  241  includes executable instructions to enter a sequence of characters corresponding to an instant message, to modify previously entered characters, to transmit a respective instant message (for example, using a Short Message Service (SMS) or Multimedia Message Service (MMS) protocol for telephony-based instant messages or using XMPP, SIMPLE, or IMPS for Internet-based instant messages), to receive instant messages, and to view received instant messages. In some embodiments, transmitted and/or received instant messages may include graphics, photos, audio files, video files and/or other attachments as are supported in an MMS and/or an Enhanced Messaging Service (EMS). As used herein, “instant messaging” refers to both telephony-based messages (e.g., messages sent using SMS or MMS) and Internet-based messages (e.g., messages sent using XMPP, SIMPLE, or IMPS). 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , text input module  234 , GPS module  235 , map module  254 , and music player module, workout support module  242  includes executable instructions to create workouts (e.g., with time, distance, and/or calorie burning goals); communicate with workout sensors (sports devices); receive workout sensor data; calibrate sensors used to monitor a workout; select and play music for a workout; and display, store, and transmit workout data. 
     In conjunction with touch screen  212 , display controller  256 , optical sensor(s)  264 , optical sensor controller  258 , contact/motion module  230 , graphics module  232 , and image management module  244 , camera module  243  includes executable instructions to capture still images or video (including a video stream) and store them into memory  202 , modify characteristics of a still image or video, or delete a still image or video from memory  202 . 
     In conjunction with touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , text input module  234 , and camera module  243 , image management module  244  includes executable instructions to arrange, modify (e.g., edit), or otherwise manipulate, label, delete, present (e.g., in a digital slide show or album), and store still and/or video images. 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , browser module  247  includes executable instructions to browse the Internet in accordance with user instructions, including searching, linking to, receiving, and displaying web pages or portions thereof, as well as attachments and other files linked to web pages. 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , text input module  234 , e-mail client module  240 , and browser module  247 , calendar module  248  includes executable instructions to create, display, modify, and store calendars and data associated with calendars (e.g., calendar entries, to-do lists, etc.) in accordance with user instructions. 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , text input module  234 , and browser module  247 , widget modules  249  are mini-applications that may be downloaded and used by a user (e.g., weather widget  249 - 1 , stocks widget  249 - 2 , calculator widget  249 - 3 , alarm clock widget  249 - 4 , and dictionary widget  249 - 5 ) or created by the user (e.g., user-created widget  249 - 6 ). In some embodiments, a widget includes an HTML (Hypertext Markup Language) file, a CSS (Cascading Style Sheets) file, and a JavaScript file. In some embodiments, a widget includes an XML (Extensible Markup Language) file and a JavaScript file (e.g., Yahoo! Widgets). 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , text input module  234 , and browser module  247 , the widget creator module  250  may be used by a user to create widgets (e.g., turning a user-specified portion of a web page into a widget). 
     In conjunction with touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , search module  251  includes executable instructions to search for text, music, sound, image, video, and/or other files in memory  202  that match one or more search criteria (e.g., one or more user-specified search terms) in accordance with user instructions. 
     In conjunction with touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , audio circuitry  210 , speaker  211 , RF circuitry  208 , and browser module  247 , video and music player module  252  includes executable instructions that allow the user to download and play back recorded music and other sound files stored in one or more file formats, such as MP3 or AAC files, and executable instructions to display, present, or otherwise play back videos (e.g., on touch screen  212  or on an external, connected display via external port  224 ). In some embodiments, device  200  optionally includes the functionality of an MP3 player, such as an iPod (trademark of Apple Inc.). 
     In conjunction with touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , and text input module  234 , notes module  253  includes executable instructions to create and manage notes, to-do lists, and the like in accordance with user instructions. 
     In conjunction with RF circuitry  208 , touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , text input module  234 , GPS module  235 , and browser module  247 , map module  254  may be used to receive, display, modify, and store maps and data associated with maps (e.g., driving directions, data on stores and other points of interest at or near a particular location, and other location-based data) in accordance with user instructions. 
     In conjunction with touch screen  212 , display controller  256 , contact/motion module  230 , graphics module  232 , audio circuitry  210 , speaker  211 , RF circuitry  208 , text input module  234 , e-mail client module  240 , and browser module  247 , online video module  255  includes instructions that allow the user to access, browse, receive (e.g., by streaming and/or download), play back (e.g., on the touch screen or on an external, connected display via external port  224 ), send an e-mail with a link to a particular online video, and otherwise manage online videos in one or more file formats, such as H.264. In some embodiments, instant messaging module  241 , rather than e-mail client module  240 , is used to send a link to a particular online video. Additional description of the online video application can be found in U.S. Provisional Patent Application No. 60/936,562, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Jun. 20, 2007, and U.S. patent application Ser. No. 11/968,067, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Dec. 31, 2007, the contents of which are hereby incorporated by reference in their entirety. 
     Each of the above-identified modules and applications corresponds to a set of executable instructions for performing one or more functions described above and the methods described in this application (e.g., the computer-implemented methods and other information processing methods described herein). These modules (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments. For example, video player module may be combined with music player module into a single module (e.g., video and music player module  252 ,  FIG. 2A ). In some embodiments, memory  202  may store a subset of the modules and data structures identified above. Furthermore, memory  202  may store additional modules and data structures not described above. 
     In some embodiments, device  200  is a device where operation of a predefined set of functions on the device is performed exclusively through a touch screen and/or a touchpad. By using a touch screen and/or a touchpad as the primary input control device for operation of device  200 , the number of physical input control devices (such as push buttons, dials, and the like) on device  200  may be reduced. 
     The predefined set of functions that are performed exclusively through a touch screen and/or a touchpad optionally include navigation between user interfaces. In some embodiments, the touchpad, when touched by the user, navigates device  200  to a main, home, or root menu from any user interface that is displayed on device  200 . In such embodiments, a “menu button” is implemented using a touchpad. In some other embodiments, the menu button is a physical push button or other physical input control device instead of a touchpad. 
       FIG. 2B  is a block diagram illustrating exemplary components for event handling in accordance with some embodiments. In some embodiments, memory  202  ( FIG. 2A ) or  470  ( FIG. 4 ) includes event sorter  270  (e.g., in operating system  226 ) and a respective application  236 - 1  (e.g., any of the aforementioned applications  237 - 251 ,  255 ,  480 - 490 ). 
     Event sorter  270  receives event information and determines the application  236 - 1  and application view  291  of application  236 - 1  to which to deliver the event information. Event sorter  270  includes event monitor  271  and event dispatcher module  274 . In some embodiments, application  236 - 1  includes application internal state  292 , which indicates the current application view(s) displayed on touch-sensitive display  212  when the application is active or executing. In some embodiments, device/global internal state  257  is used by event sorter  270  to determine which application(s) is (are) currently active, and application internal state  292  is used by event sorter  270  to determine application views  291  to which to deliver event information. 
     In some embodiments, application internal state  292  includes additional information, such as one or more of: resume information to be used when application  236 - 1  resumes execution, user interface state information that indicates information being displayed or that is ready for display by application  236 - 1 , a state queue for enabling the user to go back to a prior state or view of application  236 - 1 , and a redo/undo queue of previous actions taken by the user. 
     Event monitor  271  receives event information from peripherals interface  218 . Event information includes information about a sub-event (e.g., a user touch on touch-sensitive display  212 , as part of a multi-touch gesture). Peripherals interface  218  transmits information it receives from I/O subsystem  206  or a sensor, such as proximity sensor  266 , accelerometer(s)  268 , and/or microphone  213  (through audio circuitry  210 ). Information that peripherals interface  218  receives from I/O subsystem  206  includes information from touch-sensitive display  212  or a touch-sensitive surface. 
     In some embodiments, event monitor  271  sends requests to the peripherals interface  218  at predetermined intervals. In response, peripherals interface  218  transmits event information. In other embodiments, peripherals interface  218  transmits event information only when there is a significant event (e.g., receiving an input above a predetermined noise threshold and/or for more than a predetermined duration). 
     In some embodiments, event sorter  270  also includes a hit view determination module  272  and/or an active event recognizer determination module  273 . 
     Hit view determination module  272  provides software procedures for determining where a sub-event has taken place within one or more views when touch-sensitive display  212  displays more than one view. Views are made up of controls and other elements that a user can see on the display. 
     Another aspect of the user interface associated with an application is a set of views, sometimes herein called application views or user interface windows, in which information is displayed and touch-based gestures occur. The application views (of a respective application) in which a touch is detected may correspond to programmatic levels within a programmatic or view hierarchy of the application. For example, the lowest level view in which a touch is detected may be called the hit view, and the set of events that are recognized as proper inputs may be determined based, at least in part, on the hit view of the initial touch that begins a touch-based gesture. 
     Hit view determination module  272  receives information related to sub events of a touch-based gesture. When an application has multiple views organized in a hierarchy, hit view determination module  272  identifies a hit view as the lowest view in the hierarchy which should handle the sub-event. In most circumstances, the hit view is the lowest level view in which an initiating sub-event occurs (e.g., the first sub-event in the sequence of sub-events that form an event or potential event). Once the hit view is identified by the hit view determination module  272 , the hit view typically receives all sub-events related to the same touch or input source for which it was identified as the hit view. 
     Active event recognizer determination module  273  determines which view or views within a view hierarchy should receive a particular sequence of sub-events. In some embodiments, active event recognizer determination module  273  determines that only the hit view should receive a particular sequence of sub-events. In other embodiments, active event recognizer determination module  273  determines that all views that include the physical location of a sub-event are actively involved views, and therefore determines that all actively involved views should receive a particular sequence of sub-events. In other embodiments, even if touch sub-events were entirely confined to the area associated with one particular view, views higher in the hierarchy would still remain as actively involved views. 
     Event dispatcher module  274  dispatches the event information to an event recognizer (e.g., event recognizer  280 ). In embodiments including active event recognizer determination module  273 , event dispatcher module  274  delivers the event information to an event recognizer determined by active event recognizer determination module  273 . In some embodiments, event dispatcher module  274  stores in an event queue the event information, which is retrieved by a respective event receiver  282 . 
     In some embodiments, operating system  226  includes event sorter  270 . Alternatively, application  236 - 1  includes event sorter  270 . In yet other embodiments, event sorter  270  is a stand-alone module, or a part of another module stored in memory  202 , such as contact/motion module  230 . 
     In some embodiments, application  236 - 1  includes a plurality of event handlers  290  and one or more application views  291 , each of which includes instructions for handling touch events that occur within a respective view of the application&#39;s user interface. Each application view  291  of the application  236 - 1  includes one or more event recognizers  280 . Typically, a respective application view  291  includes a plurality of event recognizers  280 . In other embodiments, one or more of event recognizers  280  are part of a separate module, such as a user interface kit (not shown) or a higher level object from which application  236 - 1  inherits methods and other properties. In some embodiments, a respective event handler  290  includes one or more of: data updater  276 , object updater  277 , GUI updater  278 , and/or event data  279  received from event sorter  270 . Event handler  290  may utilize or call data updater  276 , object updater  277 , or GUI updater  278  to update the application internal state  292 . Alternatively, one or more of the application views  291  include one or more respective event handlers  290 . Also, in some embodiments, one or more of data updater  276 , object updater  277 , and GUI updater  278  are included in a respective application view  291 . 
     A respective event recognizer  280  receives event information (e.g., event data  279 ) from event sorter  270  and identifies an event from the event information. Event recognizer  280  includes event receiver  282  and event comparator  284 . In some embodiments, event recognizer  280  also includes at least a subset of: metadata  283 , and event delivery instructions  288  (which may include sub-event delivery instructions). 
     Event receiver  282  receives event information from event sorter  270 . The event information includes information about a sub-event, for example, a touch or a touch movement. Depending on the sub-event, the event information also includes additional information, such as location of the sub-event. When the sub-event concerns motion of a touch, the event information may also include speed and direction of the sub-event. In some embodiments, events include rotation of the device from one orientation to another (e.g., from a portrait orientation to a landscape orientation, or vice versa), and the event information includes corresponding information about the current orientation (also called device attitude) of the device. 
     Event comparator  284  compares the event information to predefined event or sub-event definitions and, based on the comparison, determines an event or sub event, or determines or updates the state of an event or sub-event. In some embodiments, event comparator  284  includes event definitions  286 . Event definitions  286  contain definitions of events (e.g., predefined sequences of sub-events), for example, event  1  ( 287 - 1 ), event  2  ( 287 - 2 ), and others. In some embodiments, sub-events in an event ( 287 ) include, for example, touch begin, touch end, touch movement, touch cancellation, and multiple touching. In one example, the definition for event  1  ( 287 - 1 ) is a double tap on a displayed object. The double tap, for example, comprises a first touch (touch begin) on the displayed object for a predetermined phase, a first liftoff (touch end) for a predetermined phase, a second touch (touch begin) on the displayed object for a predetermined phase, and a second liftoff (touch end) for a predetermined phase. In another example, the definition for event  2  ( 287 - 2 ) is a dragging on a displayed object. The dragging, for example, comprises a touch (or contact) on the displayed object for a predetermined phase, a movement of the touch across touch-sensitive display  212 , and liftoff of the touch (touch end). In some embodiments, the event also includes information for one or more associated event handlers  290 . 
     In some embodiments, event definition  287  includes a definition of an event for a respective user-interface object. In some embodiments, event comparator  284  performs a hit test to determine which user-interface object is associated with a sub-event. For example, in an application view in which three user-interface objects are displayed on touch-sensitive display  212 , when a touch is detected on touch-sensitive display  212 , event comparator  284  performs a hit test to determine which of the three user-interface objects is associated with the touch (sub-event). If each displayed object is associated with a respective event handler  290 , the event comparator uses the result of the hit test to determine which event handler  290  should be activated. For example, event comparator  284  selects an event handler associated with the sub-event and the object triggering the hit test. 
     In some embodiments, the definition for a respective event ( 287 ) also includes delayed actions that delay delivery of the event information until after it has been determined whether the sequence of sub-events does or does not correspond to the event recognizer&#39;s event type. 
     When a respective event recognizer  280  determines that the series of sub-events do not match any of the events in event definitions  286 , the respective event recognizer  280  enters an event impossible, event failed, or event ended state, after which it disregards subsequent sub-events of the touch-based gesture. In this situation, other event recognizers, if any, that remain active for the hit view continue to track and process sub-events of an ongoing touch-based gesture. 
     In some embodiments, a respective event recognizer  280  includes metadata  283  with configurable properties, flags, and/or lists that indicate how the event delivery system should perform sub-event delivery to actively involved event recognizers. In some embodiments, metadata  283  includes configurable properties, flags, and/or lists that indicate how event recognizers may interact, or are enabled to interact, with one another. In some embodiments, metadata  283  includes configurable properties, flags, and/or lists that indicate whether sub-events are delivered to varying levels in the view or programmatic hierarchy. 
     In some embodiments, a respective event recognizer  280  activates event handler  290  associated with an event when one or more particular sub-events of an event are recognized. In some embodiments, a respective event recognizer  280  delivers event information associated with the event to event handler  290 . Activating an event handler  290  is distinct from sending (and deferred sending) sub-events to a respective hit view. In some embodiments, event recognizer  280  throws a flag associated with the recognized event, and event handler  290  associated with the flag catches the flag and performs a predefined process. 
     In some embodiments, event delivery instructions  288  include sub-event delivery instructions that deliver event information about a sub-event without activating an event handler. Instead, the sub-event delivery instructions deliver event information to event handlers associated with the series of sub-events or to actively involved views. Event handlers associated with the series of sub-events or with actively involved views receive the event information and perform a predetermined process. 
     In some embodiments, data updater  276  creates and updates data used in application  236 - 1 . For example, data updater  276  updates the telephone number used in contacts module  237 , or stores a video file used in video player module. In some embodiments, object updater  277  creates and updates objects used in application  236 - 1 . For example, object updater  277  creates a new user-interface object or updates the position of a user-interface object. GUI updater  278  updates the GUI. For example, GUI updater  278  prepares display information and sends it to graphics module  232  for display on a touch-sensitive display. 
     In some embodiments, event handler(s)  290  includes or has access to data updater  276 , object updater  277 , and GUI updater  278 . In some embodiments, data updater  276 , object updater  277 , and GUI updater  278  are included in a single module of a respective application  236 - 1  or application view  291 . In other embodiments, they are included in two or more software modules. 
     It shall be understood that the foregoing discussion regarding event handling of user touches on touch-sensitive displays also applies to other forms of user inputs to operate multifunction devices  200  with input devices, not all of which are initiated on touch screens. For example, mouse movement and mouse button presses, optionally coordinated with single or multiple keyboard presses or holds; contact movements such as taps, drags, scrolls, etc. on touchpads; pen stylus inputs; movement of the device; oral instructions; detected eye movements; biometric inputs; and/or any combination thereof are optionally utilized as inputs corresponding to sub-events which define an event to be recognized. 
       FIG. 3  illustrates a portable multifunction device  200  having a touch screen  212  in accordance with some embodiments. The touch screen optionally displays one or more graphics within user interface (UI)  300 . In this embodiment, as well as others described below, a user is enabled to select one or more of the graphics by making a gesture on the graphics, for example, with one or more fingers  302  (not drawn to scale in the figure) or one or more styluses  303  (not drawn to scale in the figure). In some embodiments, selection of one or more graphics occurs when the user breaks contact with the one or more graphics. In some embodiments, the gesture optionally includes one or more taps, one or more swipes (from left to right, right to left, upward and/or downward), and/or a rolling of a finger (from right to left, left to right, upward and/or downward) that has made contact with device  200 . In some implementations or circumstances, inadvertent contact with a graphic does not select the graphic. For example, a swipe gesture that sweeps over an application icon optionally does not select the corresponding application when the gesture corresponding to selection is a tap. 
     Device  200  may also include one or more physical buttons, such as “home” or menu button  304 . As described previously, menu button  304  may be used to navigate to any application  236  in a set of applications that may be executed on device  200 . Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed on touch screen  212 . 
     In one embodiment, device  200  includes touch screen  212 , menu button  304 , push button  306  for powering the device on/off and locking the device, volume adjustment button(s)  308 , subscriber identity module (SIM) card slot  310 , headset jack  312 , and docking/charging external port  224 . Push button  306  is, optionally, used to turn the power on/off on the device by depressing the button and holding the button in the depressed state for a predefined time interval; to lock the device by depressing the button and releasing the button before the predefined time interval has elapsed; and/or to unlock the device or initiate an unlock process. In an alternative embodiment, device  200  also accepts verbal input for activation or deactivation of some functions through microphone  213 . Device  200  also, optionally, includes one or more contact intensity sensors  265  for detecting intensity of contacts on touch screen  212  and/or one or more tactile output generators  267  for generating tactile outputs for a user of device  200 . 
       FIG. 4  is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface in accordance with some embodiments. Device  400  need not be portable. In some embodiments, device  400  is a laptop computer, a desktop computer, a tablet computer, a multimedia player device, a navigation device, an educational device (such as a child&#39;s learning toy), a gaming system, or a control device (e.g., a home or industrial controller). Device  400  typically includes one or more processing units (CPUs)  410 , one or more network or other communications interfaces  460 , memory  470 , and one or more communication buses  420  for interconnecting these components. Communication buses  420  optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components. Device  400  includes input/output (I/O) interface  430  comprising display  440 , which is typically a touch screen display. I/O interface  430  also optionally includes a keyboard and/or mouse (or other pointing device)  450  and touchpad  455 , tactile output generator  457  for generating tactile outputs on device  400  (e.g., similar to tactile output generator(s)  267  described above with reference to  FIG. 2A ), sensors  459  (e.g., optical, acceleration, proximity, touch-sensitive, and/or contact intensity sensors similar to contact intensity sensor(s)  265  described above with reference to  FIG. 2A ). Memory  470  includes high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid state memory devices; and optionally includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory  470  optionally includes one or more storage devices remotely located from CPU(s)  410 . In some embodiments, memory  470  stores programs, modules, and data structures analogous to the programs, modules, and data structures stored in memory  202  of portable multifunction device  200  ( FIG. 2A ), or a subset thereof. Furthermore, memory  470  optionally stores additional programs, modules, and data structures not present in memory  202  of portable multifunction device  200 . For example, memory  470  of device  400  optionally stores drawing module  480 , presentation module  482 , word processing module  484 , website creation module  486 , disk authoring module  488 , and/or spreadsheet module  490 , while memory  202  of portable multifunction device  200  ( FIG. 2A ) optionally does not store these modules. 
     Each of the above-identified elements in  FIG. 4  may be stored in one or more of the previously mentioned memory devices. Each of the above-identified modules corresponds to a set of instructions for performing a function described above. The above-identified modules or programs (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments. In some embodiments, memory  470  may store a subset of the modules and data structures identified above. Furthermore, memory  470  may store additional modules and data structures not described above. 
     Attention is now directed towards embodiments of user interfaces that may be implemented on, for example, portable multifunction device  200 . 
       FIG. 5A  illustrates an exemplary user interface for a menu of applications on portable multifunction device  200  in accordance with some embodiments. Similar user interfaces may be implemented on device  400 . In some embodiments, user interface  500  includes the following elements, or a subset or superset thereof: 
     Signal strength indicator(s)  502  for wireless communication(s), such as cellular and Wi-Fi signals;
         Time  504 ;   Bluetooth indicator  505 ;   Battery status indicator  506 ;   Tray  508  with icons for frequently used applications, such as:
           Icon  516  for telephone module  238 , labeled “Phone,” which optionally includes an indicator  514  of the number of missed calls or voicemail messages;   Icon  518  for e-mail client module  240 , labeled “Mail,” which optionally includes an indicator  510  of the number of unread e-mails;   Icon  520  for browser module  247 , labeled “Browser;” and   Icon  522  for video and music player module  252 , also referred to as iPod (trademark of Apple Inc.) module  252 , labeled “iPod;” and   
           Icons for other applications, such as:
           Icon  524  for IM module  241 , labeled “Messages;”   Icon  526  for calendar module  248 , labeled “Calendar;”   Icon  528  for image management module  244 , labeled “Photos;”   Icon  530  for camera module  243 , labeled “Camera;”   Icon  532  for online video module  255 , labeled “Online Video;”   Icon  534  for stocks widget  249 - 2 , labeled “Stocks;”   Icon  536  for map module  254 , labeled “Maps;”   Icon  538  for weather widget  249 - 1 , labeled “Weather;”   Icon  540  for alarm clock widget  249 - 4 , labeled “Clock;”   Icon  542  for workout support module  242 , labeled “Workout Support;”   Icon  544  for notes module  253 , labeled “Notes;” and   Icon  546  for a settings application or module, labeled “Settings,” which provides access to settings for device  200  and its various applications  236 .   
               

     It should be noted that the icon labels illustrated in  FIG. 5A  are merely exemplary. For example, icon  522  for video and music player module  252  may optionally be labeled “Music” or “Music Player.” Other labels are, optionally, used for various application icons. In some embodiments, a label for a respective application icon includes a name of an application corresponding to the respective application icon. In some embodiments, a label for a particular application icon is distinct from a name of an application corresponding to the particular application icon. 
       FIG. 5B  illustrates an exemplary user interface on a device (e.g., device  400 ,  FIG. 4 ) with a touch-sensitive surface  551  (e.g., a tablet or touchpad  455 ,  FIG. 4 ) that is separate from the display  550  (e.g., touch screen display  212 ). Device  400  also, optionally, includes one or more contact intensity sensors (e.g., one or more of sensors  457 ) for detecting intensity of contacts on touch-sensitive surface  551  and/or one or more tactile output generators  459  for generating tactile outputs for a user of device  400 . 
     Although some of the examples which follow will be given with reference to inputs on touch screen display  212  (where the touch-sensitive surface and the display are combined), in some embodiments, the device detects inputs on a touch-sensitive surface that is separate from the display, as shown in  FIG. 5B . In some embodiments, the touch-sensitive surface (e.g.,  551  in  FIG. 5B ) has a primary axis (e.g.,  552  in  FIG. 5B ) that corresponds to a primary axis (e.g.,  553  in  FIG. 5B ) on the display (e.g.,  550 ). In accordance with these embodiments, the device detects contacts (e.g.,  560  and  562  in  FIG. 5B ) with the touch-sensitive surface  551  at locations that correspond to respective locations on the display (e.g., in  FIG. 5B, 560  corresponds to  568  and  562  corresponds to  570 ). In this way, user inputs (e.g., contacts  560  and  562 , and movements thereof) detected by the device on the touch-sensitive surface (e.g.,  551  in  FIG. 5B ) are used by the device to manipulate the user interface on the display (e.g.,  550  in  FIG. 5B ) of the multifunction device when the touch-sensitive surface is separate from the display. It should be understood that similar methods are, optionally, used for other user interfaces described herein. 
     Additionally, while the following examples are given primarily with reference to finger inputs (e.g., finger contacts, finger tap gestures, finger swipe gestures), it should be understood that, in some embodiments, one or more of the finger inputs are replaced with input from another input device (e.g., a mouse-based input or stylus input). For example, a swipe gesture is, optionally, replaced with a mouse click (e.g., instead of a contact) followed by movement of the cursor along the path of the swipe (e.g., instead of movement of the contact). As another example, a tap gesture is, optionally, replaced with a mouse click while the cursor is located over the location of the tap gesture (e.g., instead of detection of the contact followed by ceasing to detect the contact). Similarly, when multiple user inputs are simultaneously detected, it should be understood that multiple computer mice are, optionally, used simultaneously, or a mouse and finger contacts are, optionally, used simultaneously. 
       FIG. 6A  illustrates exemplary personal electronic device  600 . Device  600  includes body  602 . In some embodiments, device  600  can include some or all of the features described with respect to devices  200  and  400  (e.g.,  FIGS. 2A-4B ). In some embodiments, device  600  has touch-sensitive display screen  604 , hereafter touch screen  604 . Alternatively, or in addition to touch screen  604 , device  600  has a display and a touch-sensitive surface. As with devices  200  and  400 , in some embodiments, touch screen  604  (or the touch-sensitive surface) may have one or more intensity sensors for detecting intensity of contacts (e.g., touches) being applied. The one or more intensity sensors of touch screen  604  (or the touch-sensitive surface) can provide output data that represents the intensity of touches. The user interface of device  600  can respond to touches based on their intensity, meaning that touches of different intensities can invoke different user interface operations on device  600 . 
     Techniques for detecting and processing touch intensity may be found, for example, in related applications: International Patent Application Serial No. PCT/US2013/040061, titled “Device, Method, and Graphical User Interface for Displaying User Interface Objects Corresponding to an Application,” filed May 8, 2013, and International Patent Application Serial No. PCT/US2013/069483, titled “Device, Method, and Graphical User Interface for Transitioning Between Touch Input to Display Output Relationships,” filed Nov. 11, 2013, each of which is hereby incorporated by reference in their entirety. 
     In some embodiments, device  600  has one or more input mechanisms  606  and  608 . Input mechanisms  606  and  608 , if included, can be physical. Examples of physical input mechanisms include push buttons and rotatable mechanisms. In some embodiments, device  600  has one or more attachment mechanisms. Such attachment mechanisms, if included, can permit attachment of device  600  with, for example, hats, eyewear, earrings, necklaces, shirts, jackets, bracelets, watch straps, chains, trousers, belts, shoes, purses, backpacks, and so forth. These attachment mechanisms may permit device  600  to be worn by a user. 
       FIG. 6B  depicts exemplary personal electronic device  600 . In some embodiments, device  600  can include some or all of the components described with respect to  FIGS. 2A, 2B , and  4 . Device  600  has bus  612  that operatively couples I/O section  614  with one or more computer processors  616  and memory  618 . I/O section  614  can be connected to display  604 , which can have touch-sensitive component  622  and, optionally, touch-intensity sensitive component  624 . In addition, I/O section  614  can be connected with communication unit  630  for receiving application and operating system data, using Wi-Fi, Bluetooth, near field communication (NFC), cellular, and/or other wireless communication techniques. Device  600  can include input mechanisms  606  and/or  608 . Input mechanism  606  may be a rotatable input device or a depressible and rotatable input device, for example. Input mechanism  608  may be a button, in some examples. 
     Input mechanism  608  may be a microphone, in some examples. Personal electronic device  600  can include various sensors, such as GPS sensor  632 , accelerometer  634 , directional sensor  640  (e.g., compass), gyroscope  636 , motion sensor  638 , and/or a combination thereof, all of which can be operatively connected to I/O section  614 . 
     Memory  618  of personal electronic device  600  can be a non-transitory computer-readable storage medium, for storing computer-executable instructions, which, when executed by one or more computer processors  616 , for example, can cause the computer processors to perform the techniques described below, including processes  900 ,  940  and  980  ( FIGS. 9A-9H ). The computer-executable instructions can also be stored and/or transported within any non-transitory computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For purposes of this document, a “non-transitory computer-readable storage medium” can be any medium that can tangibly contain or store computer-executable instructions for use by or in connection with the instruction execution system, apparatus, or device. The non-transitory computer-readable storage medium can include, but is not limited to, magnetic, optical, and/or semiconductor storages. Examples of such storage include magnetic disks, optical discs based on CD, DVD, or Blu-ray technologies, as well as persistent solid-state memory such as flash, solid-state drives, and the like. Personal electronic device  600  is not limited to the components and configuration of  FIG. 6B , but can include other or additional components in multiple configurations. 
     As used here, the term “affordance” refers to a user-interactive graphical user interface object that may be displayed on the display screen of devices  200 ,  400 , and/or  600  ( FIGS. 2, 4, and 6 ). For example, an image (e.g., icon), a button, and text (e.g., hyperlink) may each constitute an affordance. 
     As used herein, the term “focus selector” refers to an input element that indicates a current part of a user interface with which a user is interacting. In some implementations that include a cursor or other location marker, the cursor acts as a “focus selector” so that when an input (e.g., a press input) is detected on a touch-sensitive surface (e.g., touchpad  455  in  FIG. 4  or touch-sensitive surface  551  in  FIG. 5B ) while the cursor is over a particular user interface element (e.g., a button, window, slider or other user interface element), the particular user interface element is adjusted in accordance with the detected input. In some implementations that include a touch screen display (e.g., touch-sensitive display system  212  in  FIG. 2A  or touch screen  212  in  FIG. 5A ) that enables direct interaction with user interface elements on the touch screen display, a detected contact on the touch screen acts as a “focus selector” so that when an input (e.g., a press input by the contact) is detected on the touch screen display at a location of a particular user interface element (e.g., a button, window, slider, or other user interface element), the particular user interface element is adjusted in accordance with the detected input. In some implementations, focus is moved from one region of a user interface to another region of the user interface without corresponding movement of a cursor or movement of a contact on a touch screen display (e.g., by using a tab key or arrow keys to move focus from one button to another button); in these implementations, the focus selector moves in accordance with movement of focus between different regions of the user interface. Without regard to the specific form taken by the focus selector, the focus selector is generally the user interface element (or contact on a touch screen display) that is controlled by the user so as to communicate the user&#39;s intended interaction with the user interface (e.g., by indicating, to the device, the element of the user interface with which the user is intending to interact). For example, the location of a focus selector (e.g., a cursor, a contact, or a selection box) over a respective button while a press input is detected on the touch-sensitive surface (e.g., a touchpad or touch screen) will indicate that the user is intending to activate the respective button (as opposed to other user interface elements shown on a display of the device). 
     As used in the specification and claims, the term “characteristic intensity” of a contact refers to a characteristic of the contact based on one or more intensities of the contact. In some embodiments, the characteristic intensity is based on multiple intensity samples. The characteristic intensity is, optionally, based on a predefined number of intensity samples, or a set of intensity samples collected during a predetermined time period (e.g., 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10 seconds) relative to a predefined event (e.g., after detecting the contact, prior to detecting liftoff of the contact, before or after detecting a start of movement of the contact, prior to detecting an end of the contact, before or after detecting an increase in intensity of the contact, and/or before or after detecting a decrease in intensity of the contact). A characteristic intensity of a contact is, optionally based on one or more of: a maximum value of the intensities of the contact, a mean value of the intensities of the contact, an average value of the intensities of the contact, a top 10 percentile value of the intensities of the contact, a value at the half maximum of the intensities of the contact, a value at the 90 percent maximum of the intensities of the contact, or the like. In some embodiments, the duration of the contact is used in determining the characteristic intensity (e.g., when the characteristic intensity is an average of the intensity of the contact over time). In some embodiments, the characteristic intensity is compared to a set of one or more intensity thresholds to determine whether an operation has been performed by a user. For example, the set of one or more intensity thresholds may include a first intensity threshold and a second intensity threshold. In this example, a contact with a characteristic intensity that does not exceed the first threshold results in a first operation, a contact with a characteristic intensity that exceeds the first intensity threshold and does not exceed the second intensity threshold results in a second operation, and a contact with a characteristic intensity that exceeds the second threshold results in a third operation. In some embodiments, a comparison between the characteristic intensity and one or more thresholds is used to determine whether or not to perform one or more operations (e.g., whether to perform a respective operation or forgo performing the respective operation) rather than being used to determine whether to perform a first operation or a second operation. 
     In some embodiments, a portion of a gesture is identified for purposes of determining a characteristic intensity. For example, a touch-sensitive surface may receive a continuous swipe contact transitioning from a start location and reaching an end location, at which point the intensity of the contact increases. In this example, the characteristic intensity of the contact at the end location may be based on only a portion of the continuous swipe contact, and not the entire swipe contact (e.g., only the portion of the swipe contact at the end location). In some embodiments, a smoothing algorithm may be applied to the intensities of the swipe contact prior to determining the characteristic intensity of the contact. For example, the smoothing algorithm optionally includes one or more of: an unweighted sliding-average smoothing algorithm, a triangular smoothing algorithm, a median filter smoothing algorithm, and/or an exponential smoothing algorithm. In some circumstances, these smoothing algorithms eliminate narrow spikes or dips in the intensities of the swipe contact for purposes of determining a characteristic intensity. 
     The intensity of a contact on the touch-sensitive surface may be characterized relative to one or more intensity thresholds, such as a contact-detection intensity threshold, a light press intensity threshold, a deep press intensity threshold, and/or one or more other intensity thresholds. In some embodiments, the light press intensity threshold corresponds to an intensity at which the device will perform operations typically associated with clicking a button of a physical mouse or a trackpad. In some embodiments, the deep press intensity threshold corresponds to an intensity at which the device will perform operations that are different from operations typically associated with clicking a button of a physical mouse or a trackpad. In some embodiments, when a contact is detected with a characteristic intensity below the light press intensity threshold (e.g., and above a nominal contact-detection intensity threshold below which the contact is no longer detected), the device will move a focus selector in accordance with movement of the contact on the touch-sensitive surface without performing an operation associated with the light press intensity threshold or the deep press intensity threshold. Generally, unless otherwise stated, these intensity thresholds are consistent between different sets of user interface figures. 
     An increase of characteristic intensity of the contact from an intensity below the light press intensity threshold to an intensity between the light press intensity threshold and the deep press intensity threshold is sometimes referred to as a “light press” input. An increase of characteristic intensity of the contact from an intensity below the deep press intensity threshold to an intensity above the deep press intensity threshold is sometimes referred to as a “deep press” input. An increase of characteristic intensity of the contact from an intensity below the contact-detection intensity threshold to an intensity between the contact-detection intensity threshold and the light press intensity threshold is sometimes referred to as detecting the contact on the touch-surface. A decrease of characteristic intensity of the contact from an intensity above the contact-detection intensity threshold to an intensity below the contact-detection intensity threshold is sometimes referred to as detecting liftoff of the contact from the touch-surface. In some embodiments, the contact-detection intensity threshold is zero. In some embodiments, the contact-detection intensity threshold is greater than zero. 
     In some embodiments described herein, one or more operations are performed in response to detecting a gesture that includes a respective press input or in response to detecting the respective press input performed with a respective contact (or a plurality of contacts), where the respective press input is detected based at least in part on detecting an increase in intensity of the contact (or plurality of contacts) above a press-input intensity threshold. In some embodiments, the respective operation is performed in response to detecting the increase in intensity of the respective contact above the press-input intensity threshold (e.g., a “down stroke” of the respective press input). In some embodiments, the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the press-input threshold (e.g., an “up stroke” of the respective press input). 
     In some embodiments, the device employs intensity hysteresis to avoid accidental inputs sometimes termed “jitter,” where the device defines or selects a hysteresis intensity threshold with a predefined relationship to the press-input intensity threshold (e.g., the hysteresis intensity threshold is X intensity units lower than the press-input intensity threshold or the hysteresis intensity threshold is 75%, 90%, or some reasonable proportion of the press-input intensity threshold). Thus, in some embodiments, the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the hysteresis intensity threshold that corresponds to the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the hysteresis intensity threshold (e.g., an “up stroke” of the respective press input). Similarly, in some embodiments, the press input is detected only when the device detects an increase in intensity of the contact from an intensity at or below the hysteresis intensity threshold to an intensity at or above the press-input intensity threshold and, optionally, a subsequent decrease in intensity of the contact to an intensity at or below the hysteresis intensity, and the respective operation is performed in response to detecting the press input (e.g., the increase in intensity of the contact or the decrease in intensity of the contact, depending on the circumstances). 
     For ease of explanation, the descriptions of operations performed in response to a press input associated with a press-input intensity threshold or in response to a gesture including the press input are, optionally, triggered in response to detecting either: an increase in intensity of a contact above the press-input intensity threshold, an increase in intensity of a contact from an intensity below the hysteresis intensity threshold to an intensity above the press-input intensity threshold, a decrease in intensity of the contact below the press-input intensity threshold, and/or a decrease in intensity of the contact below the hysteresis intensity threshold corresponding to the press-input intensity threshold. Additionally, in examples where an operation is described as being performed in response to detecting a decrease in intensity of a contact below the press-input intensity threshold, the operation is, optionally, performed in response to detecting a decrease in intensity of the contact below a hysteresis intensity threshold corresponding to, and lower than, the press-input intensity threshold. 
     2. Digital Assistant System 
       FIG. 7A  illustrates a block diagram of digital assistant system  700  in accordance with various examples. In some examples, digital assistant system  700  can be implemented on a standalone computer system. In some examples, digital assistant system  700  can be distributed across multiple computers. In some examples, some of the modules and functions of the digital assistant can be divided into a server portion and a client portion, where the client portion resides on one or more user devices (e.g., devices  104 ,  122 ,  200 ,  400 , or  600 ) and communicates with the server portion (e.g., server system  108 ) through one or more networks, e.g., as shown in  FIG. 1 . In some examples, digital assistant system  700  can be an implementation of server system  108  (and/or DA server  106 ) shown in  FIG. 1 . It should be noted that digital assistant system  700  is only one example of a digital assistant system, and that digital assistant system  700  can have more or fewer components than shown, may combine two or more components, or may have a different configuration or arrangement of the components. The various components shown in  FIG. 7A  can be implemented in hardware, software instructions for execution by one or more processors, firmware, including one or more signal processing and/or application specific integrated circuits, or a combination thereof. 
     Digital assistant system  700  can include memory  702 , one or more processors  704 , input/output (I/O) interface  706 , and network communications interface  708 . These components can communicate with one another over one or more communication buses or signal lines  710 . 
     In some examples, memory  702  can include a non-transitory computer-readable medium, such as high-speed random access memory and/or a non-volatile computer-readable storage medium (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices). 
     In some examples, I/O interface  706  can couple input/output devices  716  of digital assistant system  700 , such as displays, keyboards, touch screens, and microphones, to user interface module  722 . I/O interface  706 , in conjunction with user interface module  722 , can receive user inputs (e.g., voice input, keyboard inputs, touch inputs, etc.) and processes them accordingly. In some examples, e.g., when the digital assistant is implemented on a standalone user device, digital assistant system  700  can include any of the components and I/O communication interfaces described with respect to devices  200 ,  400 , or  600  in  FIGS. 2A, 4, 6A -B, respectively. In some examples, digital assistant system  700  can represent the server portion of a digital assistant implementation, and can interact with the user through a client-side portion residing on a user device (e.g., devices  104 ,  200 ,  400 , or  600 ). 
     In some examples, the network communications interface  708  can include wired communication port(s)  712  and/or wireless transmission and reception circuitry  714 . The wired communication port(s) can receive and send communication signals via one or more wired interfaces, e.g., Ethernet, Universal Serial Bus (USB), FIREWIRE, etc. The wireless circuitry  714  can receive and send RF signals and/or optical signals from/to communications networks and other communications devices. The wireless communications can use any of a plurality of communications standards, protocols, and technologies, such as GSM, EDGE, CDMA, TDMA, Bluetooth, Wi-Fi, VoIP, Wi-MAX, or any other suitable communication protocol. Network communications interface  708  can enable communication between digital assistant system  700  with networks, such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices. 
     In some examples, memory  702 , or the computer-readable storage media of memory  702 , can store programs, modules, instructions, and data structures including all or a subset of: operating system  718 , communications module  720 , user interface module  722 , one or more applications  724 , and digital assistant module  726 . In particular, memory  702 , or the computer-readable storage media of memory  702 , can store instructions for performing method  900 , described below. One or more processors  704  can execute these programs, modules, and instructions, and reads/writes from/to the data structures. 
     Operating system  718  (e.g., Darwin, RTXC, LINUX, UNIX, iOS, OS X, WINDOWS, or an embedded operating system such as VxWorks) can include various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communications between various hardware, firmware, and software components. 
     Communications module  720  can facilitate communications between digital assistant system  700  with other devices over network communications interface  708 . For example, communications module  720  can communicate with RF circuitry  208  of electronic devices such as devices  200 ,  400 , and  600  shown in  FIG. 2A, 4, 6A -B, respectively. Communications module  720  can also include various components for handling data received by wireless circuitry  714  and/or wired communications port  712 . 
     User interface module  722  can receive commands and/or inputs from a user via I/O interface  706  (e.g., from a keyboard, touch screen, pointing device, controller, and/or microphone), and generate user interface objects on a display. User interface module  722  can also prepare and deliver outputs (e.g., speech, sound, animation, text, icons, vibrations, haptic feedback, light, etc.) to the user via the I/O interface  706  (e.g., through displays, audio channels, speakers, touch-pads, etc.). 
     Applications  724  can include programs and/or modules that are configured to be executed by one or more processors  704 . For example, if the digital assistant system is implemented on a standalone user device, applications  724  can include user applications, such as games, a calendar application, a navigation application, or an email application. If digital assistant system  700  is implemented on a server, applications  724  can include resource management applications, diagnostic applications, or scheduling applications, for example. 
     Memory  702  can also store digital assistant module  726  (or the server portion of a digital assistant). In some examples, digital assistant module  726  can include the following sub-modules, or a subset or superset thereof: input/output processing module  728 , speech-to-text (STT) processing module  730 , natural language processing module  732 , dialogue flow processing module  734 , task flow processing module  736 , service processing module  738 , and speech synthesis module  740 . Each of these modules can have access to one or more of the following systems or data and models of the digital assistant module  726 , or a subset or superset thereof: ontology  760 , vocabulary index  744 , user data  748 , task flow models  754 , service models  756 , and ASR systems. 
     In some examples, using the processing modules, data, and models implemented in digital assistant module  726 , the digital assistant can perform at least some of the following: converting speech input into text; identifying a user&#39;s intent expressed in a natural language input received from the user; actively eliciting and obtaining information needed to fully infer the user&#39;s intent (e.g., by disambiguating words, games, intentions, etc.); determining the task flow for fulfilling the inferred intent; and executing the task flow to fulfill the inferred intent. 
     In some examples, as shown in  FIG. 7B , I/O processing module  728  can interact with the user through I/O devices  716  in  FIG. 7A  or with a user device (e.g., devices  104 ,  200 ,  400 , or  600 ) through network communications interface  708  in  FIG. 7A  to obtain user input (e.g., a speech input) and to provide responses (e.g., as speech outputs) to the user input. I/O processing module  728  can optionally obtain contextual information associated with the user input from the user device, along with or shortly after the receipt of the user input. The contextual information can include user-specific data, vocabulary, and/or preferences relevant to the user input. In some examples, the contextual information also includes software and hardware states of the user device at the time the user request is received, and/or information related to the surrounding environment of the user at the time that the user request was received. In some examples, I/O processing module  728  can also send follow-up questions to, and receive answers from, the user regarding the user request. When a user request is received by I/O processing module  728  and the user request can include speech input, I/O processing module  728  can forward the speech input to STT processing module  730  (or speech recognizer) for speech-to-text conversions. 
     STT processing module  730  can include one or more ASR systems. The one or more ASR systems can process the speech input that is received through I/O processing module  728  to produce a recognition result. Each ASR system can include a front-end speech pre-processor. The front-end speech pre-processor can extract representative features from the speech input. For example, the front-end speech pre-processor can perform a Fourier transform on the speech input to extract spectral features that characterize the speech input as a sequence of representative multi-dimensional vectors. Further, each ASR system can include one or more speech recognition models (e.g., acoustic models and/or language models) and can implement one or more speech recognition engines. Examples of speech recognition models can include Hidden Markov Models, Gaussian-Mixture Models, Deep Neural Network Models, n-gram language models, and other statistical models. Examples of speech recognition engines can include the dynamic time warping based engines and weighted finite-state transducers (WFST) based engines. The one or more speech recognition models and the one or more speech recognition engines can be used to process the extracted representative features of the front-end speech pre-processor to produce intermediate recognitions results (e.g., phonemes, phonemic strings, and sub-words), and ultimately, text recognition results (e.g., words, word strings, or sequence of tokens). In some examples, the speech input can be processed at least partially by a third-party service or on the user&#39;s device (e.g., device  104 ,  200 ,  400 , or  600 ) to produce the recognition result. Once STT processing module  730  produces recognition results containing a text string (e.g., words, or sequence of words, or sequence of tokens), the recognition result can be passed to natural language processing module  732  for intent deduction. 
     More details on the speech-to-text processing are described in U.S. Utility application Ser. No. 13/236,942 for “Consolidating Speech Recognition Results,” filed on Sep. 20, 2011, the entire disclosure of which is incorporated herein by reference. 
     In some examples, STT processing module  730  can include and/or access a vocabulary of recognizable words via phonetic alphabet conversion module  731 . Each vocabulary word can be associated with one or more candidate pronunciations of the word represented in a speech recognition phonetic alphabet. In particular, the vocabulary of recognizable words can include a word that is associated with a plurality of candidate pronunciations. For example, the vocabulary may include the word “tomato” that is associated with the candidate pronunciations of   and  . Further, vocabulary words can be associated with custom candidate pronunciations that are based on previous speech inputs from the user. Such custom candidate pronunciations can be stored in STT processing module  730  and can be associated with a particular user via the user&#39;s profile on the device. In some examples, the candidate pronunciations for words can be determined based on the spelling of the word and one or more linguistic and/or phonetic rules. In some examples, the candidate pronunciations can be manually generated, e.g., based on known canonical pronunciations. 
     In some examples, the candidate pronunciations can be ranked based on the commonness of the candidate pronunciation. For example, the candidate pronunciation   can be ranked higher than  , because the former is a more commonly used pronunciation (e.g., among all users, for users in a particular geographical region, or for any other appropriate subset of users). In some examples, candidate pronunciations can be ranked based on whether the candidate pronunciation is a custom candidate pronunciation associated with the user. For example, custom candidate pronunciations can be ranked higher than canonical candidate pronunciations. This can be useful for recognizing proper nouns having a unique pronunciation that deviates from canonical pronunciation. In some examples, candidate pronunciations can be associated with one or more speech characteristics, such as geographic origin, nationality, or ethnicity. For example, the candidate pronunciation   can be associated with the United States, whereas the candidate pronunciation   can be associated with Great Britain. Further, the rank of the candidate pronunciation can be based on one or more characteristics (e.g., geographic origin, nationality, ethnicity, etc.) of the user stored in the user&#39;s profile on the device. For example, it can be determined from the user&#39;s profile that the user is associated with the United States. Based on the user being associated with the United States, the candidate pronunciation   (associated with the United States) can be ranked higher than the candidate pronunciation   (associated with Great Britain). In some examples, one of the ranked candidate pronunciations can be selected as a predicted pronunciation (e.g., the most likely pronunciation). 
     When a speech input is received, STT processing module  730  can be used to determine the phonemes corresponding to the speech input (e.g., using an acoustic model), and then attempt to determine words that match the phonemes (e.g., using a language model). For example, if STT processing module  730  can first identify the sequence of phonemes   corresponding to a portion of the speech input, it can then determine, based on vocabulary index  744 , that this sequence corresponds to the word “tomato.” 
     In some examples, STT processing module  730  can use approximate matching techniques to determine words in an utterance. Thus, for example, the STT processing module  730  can determine that the sequence of phonemes   corresponds to the word “tomato,” even if that particular sequence of phonemes is not one of the candidate sequence of phonemes for that word. 
     In some examples, natural language processing module  732  can be configured to receive metadata associated with the speech input. The metadata can indicate whether to perform natural language processing on the speech input (or the sequence of words or tokens corresponding to the speech input). If the metadata indicates that natural language processing is to be performed, then the natural language processing module can receive the sequence of words or tokens from the STT processing module to perform natural language processing. However, if the metadata indicates that natural language process is not to be performed, then the natural language processing module can be disabled and the sequence of words or tokens (e.g., text string) from the STT processing module can be outputted from the digital assistant. In some examples, the metadata can further identify one or more domains corresponding to the user request. Based on the one or more domains, the natural language processor can disable domains in ontology  760  other than the one or more domains. In this way, natural language processing is constrained to the one or more domains in ontology  760 . In particular, the structure query (described below) can be generated using the one or more domains and not the other domains in the ontology. 
     Natural language processing module  732  (“natural language processor”) of the digital assistant can take the sequence of words or tokens (“token sequence”) generated by STT processing module  730 , and attempt to associate the token sequence with one or more “actionable intents” recognized by the digital assistant. An “actionable intent” can represent a task that can be performed by the digital assistant, and can have an associated task flow implemented in task flow models  754 . The associated task flow can be a series of programmed actions and steps that the digital assistant takes in order to perform the task. The scope of a digital assistant&#39;s capabilities can be dependent on the number and variety of task flows that have been implemented and stored in task flow models  754 , or in other words, on the number and variety of “actionable intents” that the digital assistant recognizes. The effectiveness of the digital assistant, however, can also be dependent on the assistant&#39;s ability to infer the correct “actionable intent(s)” from the user request expressed in natural language. 
     In some examples, in addition to the sequence of words or tokens obtained from STT processing module  730 , natural language processing module  732  can also receive contextual information associated with the user request, e.g., from I/O processing module  728 . The natural language processing module  732  can optionally use the contextual information to clarify, supplement, and/or further define the information contained in the token sequence received from STT processing module  730 . The contextual information can include, for example, user preferences, hardware, and/or software states of the user device, sensor information collected before, during, or shortly after the user request, prior interactions (e.g., dialogue) between the digital assistant and the user, and the like. As described herein, contextual information can be dynamic, and can change with time, location, content of the dialogue, and other factors. 
     In some examples, the natural language processing can be based on, e.g., ontology  760 . Ontology  760  can be a hierarchical structure containing many nodes, each node representing either an “actionable intent” or a “property” relevant to one or more of the “actionable intents” or other “properties.” As noted above, an “actionable intent” can represent a task that the digital assistant is capable of performing, i.e., it is “actionable” or can be acted on. A “property” can represent a parameter associated with an actionable intent or a sub-aspect of another property. A linkage between an actionable intent node and a property node in ontology  760  can define how a parameter represented by the property node pertains to the task represented by the actionable intent node. 
     In some examples, ontology  760  can be made up of actionable intent nodes and property nodes. Within ontology  760 , each actionable intent node can be linked to one or more property nodes either directly or through one or more intermediate property nodes. Similarly, each property node can be linked to one or more actionable intent nodes either directly or through one or more intermediate property nodes. For example, as shown in  FIG. 7C , ontology  760  can include a “restaurant reservation” node (i.e., an actionable intent node). Property nodes “restaurant,” “date/time” (for the reservation), and “party size” can each be directly linked to the actionable intent node (i.e., the “restaurant reservation” node). 
     In addition, property nodes “cuisine,” “price range,” “phone number,” and “location” can be sub-nodes of the property node “restaurant,” and can each be linked to the “restaurant reservation” node (i.e., the actionable intent node) through the intermediate property node “restaurant.” For another example, as shown in  FIG. 7C , ontology  760  can also include a “set reminder” node (i.e., another actionable intent node). Property nodes “date/time” (for setting the reminder) and “subject” (for the reminder) can each be linked to the “set reminder” node. Since the property “date/time” can be relevant to both the task of making a restaurant reservation and the task of setting a reminder, the property node “date/time” can be linked to both the “restaurant reservation” node and the “set reminder” node in ontology  760 . 
     An actionable intent node, along with its linked concept nodes, can be described as a “domain.” In the present discussion, each domain can be associated with a respective actionable intent, and refers to the group of nodes (and the relationships there between) associated with the particular actionable intent. For example, ontology  760  shown in  FIG. 7C  can include an example of restaurant reservation domain  762  and an example of reminder domain  764  within ontology  760 . The restaurant reservation domain includes the actionable intent node “restaurant reservation,” property nodes “restaurant,” “date/time,” and “party size,” and sub-property nodes “cuisine,” “price range,” “phone number,” and “location.” Reminder domain  764  can include the actionable intent node “set reminder,” and property nodes “subject” and “date/time.” In some examples, ontology  760  can be made up of many domains. Each domain can share one or more property nodes with one or more other domains. For example, the “date/time” property node can be associated with many different domains (e.g., a scheduling domain, a travel reservation domain, a movie ticket domain, etc.), in addition to restaurant reservation domain  762  and reminder domain  764 . 
     While  FIG. 7C  illustrates two example domains within ontology  760 , other domains can include, for example, “find a movie,” “initiate a phone call,” “find directions,” “schedule a meeting,” “send a message,” and “provide an answer to a question,” “read a list,” “providing navigation instructions,” “provide instructions for a task” and so on. A “send a message” domain can be associated with a “send a message” actionable intent node, and may further include property nodes such as “recipient(s),” “message type,” and “message body.” The property node “recipient” can be further defined, for example, by the sub-property nodes such as “recipient name” and “message address.” 
     In some examples, ontology  760  can include all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon. In some examples, ontology  760  can be modified, such as by adding or removing entire domains or nodes, or by modifying relationships between the nodes within the ontology  760 . 
     In some examples, nodes associated with multiple related actionable intents can be clustered under a “super domain” in ontology  760 . For example, a “travel” super-domain can include a cluster of property nodes and actionable intent nodes related to travel. The actionable intent nodes related to travel can include “airline reservation,” “hotel reservation,” “car rental,” “get directions,” “find points of interest,” and so on. The actionable intent nodes under the same super domain (e.g., the “travel” super domain) can have many property nodes in common. For example, the actionable intent nodes for “airline reservation,” “hotel reservation,” “car rental,” “get directions,” and “find points of interest” can share one or more of the property nodes “start location,” “destination,” “departure date/time,” “arrival date/time,” and “party size.” 
     In some examples, each node in ontology  760  can be associated with a set of words and/or phrases that are relevant to the property or actionable intent represented by the node. The respective set of words and/or phrases associated with each node can be the so-called “vocabulary” associated with the node. The respective set of words and/or phrases associated with each node can be stored in vocabulary index  744  in association with the property or actionable intent represented by the node. For example, returning to  FIG. 7B , the vocabulary associated with the node for the property of “restaurant” can include words such as “food,” “drinks,” “cuisine,” “hungry,” “eat,” “pizza,” “fast food,” “meal,” and so on. For another example, the vocabulary associated with the node for the actionable intent of “initiate a phone call” can include words and phrases such as “call,” “phone,” “dial,” “ring,” “call this number,” “make a call to,” and so on. The vocabulary index  744  can optionally include words and phrases in different languages. 
     Natural language processing module  732  can receive the token sequence (e.g., a text string) from STT processing module  730 , and determine what nodes are implicated by the words in the token sequence. In some examples, if a word or phrase in the token sequence is found to be associated with one or more nodes in ontology  760  (via vocabulary index  744 ), the word or phrase can “trigger” or “activate” those nodes. Based on the quantity and/or relative importance of the activated nodes, natural language processing module  732  can select one of the actionable intents as the task that the user intended the digital assistant to perform. In some examples, the domain that has the most “triggered” nodes can be selected. In some examples, the domain having the highest confidence value (e.g., based on the relative importance of its various triggered nodes) can be selected. In some examples, the domain can be selected based on a combination of the number and the importance of the triggered nodes. In some examples, additional factors are considered in selecting the node as well, such as whether the digital assistant has previously correctly interpreted a similar request from a user. 
     User data  748  can include user-specific information, such as user-specific vocabulary, user preferences, user address, user&#39;s default and secondary languages, user&#39;s contact list, and other short-term or long-term information for each user. Natural language processing module  732  can use the user-specific information to supplement the information contained in the user input to further define the user intent. For example, for a user request “invite my friends to my birthday party,” natural language processing module  732  can be able to access user data  748  to determine who the “friends” are and when and where the “birthday party” would be held, rather than requiring the user to provide such information explicitly in his/her request, by, for example, using a list of “friends” from the user&#39;s contact list, locating a calendar entry for “birthday party” in the user&#39;s calendar or in the user&#39;s email and then sending the information to the corresponding contact information listed for each contact in the contact list. 
     Other details of searching an ontology based on a token string is described in U.S. Utility application Ser. No. 12/341,743 for “Method and Apparatus for Searching Using An Active Ontology,” filed Dec. 22, 2008, the entire disclosure of which is incorporated herein by reference. 
     In some examples, once natural language processing module  732  identifies an actionable intent (or domain) based on the user request, natural language processing module  732  can generate a structured query to represent the identified actionable intent. In some examples, the structured query can include parameters for one or more nodes within the domain for the actionable intent, and at least some of the parameters are populated with the specific information and requirements specified in the user request. For example, the user may say “Make me a dinner reservation at a sushi place at  7 .” In this case, natural language processing module  732  can be able to correctly identify the actionable intent to be “restaurant reservation” based on the user input. According to the ontology, a structured query for a “restaurant reservation” domain may include parameters such as {Cuisine}, {Time}, {Date}, {Party Size}, and the like. In some examples, based on the speech input and the text derived from the speech input using STT processing module  730 , natural language processing module  732  can generate a partial structured query for the restaurant reservation domain, where the partial structured query includes the parameters {Cuisine=“Sushi”} and {Time=“7 pm”}. However, in this example, the user&#39;s utterance contains insufficient information to complete the structured query associated with the domain. Therefore, other necessary parameters such as {Party Size} and {Date} may not be specified in the structured query based on the information currently available. In some examples, natural language processing module  732  can populate some parameters of the structured query with received contextual information. For example, in some examples, if the user requested a sushi restaurant “near me,” natural language processing module  732  can populate a {location} parameter in the structured query with GPS coordinates from the user device. 
     In some examples, natural language processing module  732  can pass the generated structured query (including any completed parameters) to task flow processing module  736  (“task flow processor”). Task flow processing module  736  can be configured to receive the structured query from natural language processing module  732 , complete the structured query, if necessary, and perform the actions required to “complete” the user&#39;s ultimate request. In some examples, the various procedures necessary to complete these tasks can be provided in task flow models  754 . In some examples, task flow models  754  can include procedures for obtaining additional information from the user and task flows for performing actions associated with the actionable intent. 
     As described above, in order to complete a structured query, task flow processing module  736  may need to initiate additional dialogue with the user in order to obtain additional information, and/or disambiguate potentially ambiguous utterances. When such interactions are necessary, task flow processing module  736  can invoke dialogue flow processing module  734  to engage in a dialogue with the user. In some examples, dialogue flow processing module  734  can determine how (and/or when) to ask the user for the additional information and receives and processes the user responses. The questions can be provided to and answers can be received from the users through I/O processing module  728 . In some examples, dialogue flow processing module  734  can present dialogue output to the user via audio and/or visual output, and receives input from the user via spoken or physical (e.g., clicking) responses. Continuing with the example above, when task flow processing module  736  invokes dialogue flow processing module  734  to determine the “party size” and “date” information for the structured query associated with the domain “restaurant reservation,” dialogue flow processing module  734  can generate questions such as “For how many people?” and “On which day?” to pass to the user. Once answers are received from the user, dialogue flow processing module  734  can then populate the structured query with the missing information, or pass the information to task flow processing module  736  to complete the missing information from the structured query. 
     Once task flow processing module  736  has completed the structured query for an actionable intent, task flow processing module  736  can proceed to perform the ultimate task associated with the actionable intent. Accordingly, task flow processing module  736  can execute the steps and instructions in the task flow model according to the specific parameters contained in the structured query. For example, the task flow model for the actionable intent of “restaurant reservation” can include steps and instructions for contacting a restaurant and actually requesting a reservation for a particular party size at a particular time. For example, using a structured query such as: {restaurant reservation, restaurant=ABC Café, date=3/12/2012, time=7 pm, party size=5}, task flow processing module  736  can perform the steps of: (1) logging onto a server of the ABC Café or a restaurant reservation system such as OPENTABLE®, (2) entering the date, time, and party size information in a form on the website, (3) submitting the form, and (4) making a calendar entry for the reservation in the user&#39;s calendar. 
     In some examples, task flow processing module  736  can employ the assistance of service processing module  738  (“service processing module”) to complete a task requested in the user input or to provide an informational answer requested in the user input. For example, service processing module  738  can act on behalf of task flow processing module  736  to make a phone call, set a calendar entry, invoke a map search, invoke or interact with other user applications installed on the user device, and invoke or interact with third-party services (e.g., a restaurant reservation portal, a social networking website, a banking portal, etc.). In some examples, the protocols and application programming interfaces (API) required by each service can be specified by a respective service model among service models  756 . Service processing module  738  can access the appropriate service model for a service and generate requests for the service in accordance with the protocols and APIs required by the service according to the service model. 
     For example, if a restaurant has enabled an online reservation service, the restaurant can submit a service model specifying the necessary parameters for making a reservation and the APIs for communicating the values of the necessary parameter to the online reservation service. When requested by task flow processing module  736 , service processing module  738  can establish a network connection with the online reservation service using the web address stored in the service model, and send the necessary parameters of the reservation (e.g., time, date, party size) to the online reservation interface in a format according to the API of the online reservation service. 
     In some examples, natural language processing module  732 , dialogue flow processing module  734 , and task flow processing module  736  can be used collectively and iteratively to infer and define the user&#39;s intent, obtain information to further clarify and refine the user intent, and finally generate a response (i.e., an output to the user, or the completion of a task) to fulfill the user&#39;s intent. The generated response can be a dialogue response to the speech input that at least partially fulfills the user&#39;s intent. Further, in some examples, the generated response can be output as a speech output. In these examples, the generated response can be sent to speech synthesis module  740  (e.g., speech synthesizer) where it can be processed to synthesize the dialogue response in speech form. In yet other examples, the generated response can be data content relevant to satisfying a user request in the speech input. 
     Speech synthesis module  740  can be configured to synthesize speech outputs for presentation to the user. Speech synthesis module  740  synthesizes speech outputs based on text provided by the digital assistant. For example, the generated dialogue response can be in the form of a text string. Speech synthesis module  740  can convert the text string to an audible speech output. Speech synthesis module  740  can use any appropriate speech synthesis technique in order to generate speech outputs from text, including, but not limited, to concatenative synthesis, unit selection synthesis, diphone synthesis, domain-specific synthesis, formant synthesis, articulatory synthesis, hidden Markov model (HMM) based synthesis, and sinewave synthesis. In some examples, speech synthesis module  740  can be configured to synthesize individual words based on phonemic strings corresponding to the words. For example, a phonemic string can be associated with a word in the generated dialogue response. The phonemic string can be stored in metadata associated with the word. Speech synthesis model  740  can be configured to directly process the phonemic string in the metadata to synthesize the word in speech form. 
     In some examples, instead of (or in addition to) using speech synthesis module  740 , speech synthesis can be performed on a remote device (e.g., the server system  108 ), and the synthesized speech can be sent to the user device for output to the user. For example, this can occur in some implementations where outputs for a digital assistant are generated at a server system. And because server systems generally have more processing power or resources than a user device, it can be possible to obtain higher quality speech outputs than would be practical with client-side synthesis. 
     Additional details on digital assistants can be found in the U.S. Utility application Ser. No. 12/987,982, entitled “Intelligent Automated Assistant,” filed Jan. 10, 2011, and U.S. Utility application Ser. No. 13/251,088, entitled “Generating and Processing Task Items That Represent Tasks to Perform,” filed Sep. 30, 2011, the entire disclosures of which are incorporated herein by reference. 
     Attention is now directed towards embodiments of user interfaces (“UI”) and associated processes that are implemented on an electronic device, such as user device  104 , portable multifunction device  200 , multifunctional device  400 , or personal electronic device  600  (collectively “electronic device  104 ,  200 ,  400 ,  600 ”). References in this document to any one particular electronic device  104 ,  200 ,  400 ,  600  shall be understood to encompass all of the electronic devices  104 ,  200 ,  400 ,  600  unless one or more of those electronic devices  104 ,  200 ,  400 ,  600  is excluded by the plain meaning of the text. 
     Referring to  FIG. 8A , an electronic device  200  includes a display  212  and a microphone  213  in accordance with some embodiments. A digital assistant, as described above, is accessed by a user, who makes a request for service from a virtual assistant. In the example of  FIG. 8A , the user utters unstructured natural language user input that is acquired via the microphone  213 . The timing of the user request is under the control of the user. In this example, user input  770  is an unstructured natural language request to “find a good sushi restaurant near me.” The user input is converted from speech to text, and in accordance with some embodiments, the textual user input  770  is displayed on the display  212 . By displaying the textual user input  770 , in accordance with some embodiments, the user can verify that the digital assistant has received correctly the request as made. In other embodiments, such as but not limited to embodiments in which the digital assistant is operable in a hands-free mode, the textual user input  770  is not displayed. The electronic device  200  of  FIG. 8A  is a smartphone, a tablet, a laptop, or other portable device, according to some embodiments. According to other embodiments, the electronic device  200  of  FIG. 8A  is a desktop computer; a device connected to a television such as an Apple TV® digital media extender of Apple, Inc., Cupertino, Calif.; or other less-portable device that generally remains in one location. 
     Referring also to  FIG. 8E , upon receiving the user request for service from the virtual assistant  700 , the DA client  102  located on the electronic device  200  determines at least one task to perform in response to the user request. In some embodiments, more than one task is performed in order to satisfy the user request. According to some embodiments, one task to perform in response to the user request is context resolution, which establishes a context associated with a user and/or the electronic device  200 . According to some embodiments, one task to perform in response to the user request is speech recognition. According to some embodiments, one task to perform in response to the user request is automatic speech recognition. According to some embodiments, one task to perform in response to the user request is domain classification. According to some embodiments, one task to perform in response to the user request is natural language parsing. “Parsing” refers to determining the grammatical structure of sentences. According to some embodiments, one task to perform in response to the user request is query resolution, which refers to determining the content of a user query. According to some embodiments, one task to perform in response to the user request is natural language synthesis. According to some embodiments, one task to perform in response to the user request is user interface resolution, which refers to determining which action a user has taken relative to a user interface. According to some embodiments, one task to perform in response to the user request is text-to-speech conversion. Each of these tasks is described earlier in this document. When the DA client  102  located on the electronic device  200  determines at least one task to perform in response to the user request, it may determine one or more tasks in addition to those explicitly listed above. 
     In this example, the DA client  102  determines that speech recognition is at least one task to perform in response to the user request. Next, the DA client  102  estimates at least one performance characteristic for completing that speech recognition task with the electronic device  200 , based on at least one heuristic. According to some embodiments, performance characteristics include speed of task performance, relative efficiency of task performance, and power consumption of task performance. According to other embodiments, a performance characteristic includes any other performance metric relevant to performance of a task. By estimating at least one performance characteristic for completing a task with the electronic device, the DA client  102  is able to determine whether the task should be performed at the electronic device  200  itself, or transmitted outside the electronic device  200  to be performed elsewhere, such as at the DA server  106 . 
     A number of heuristics may be used to determine whether a task should be completed on the electronic device  200 , on a server, or completed partially on the device  200  and partially on the server. As will be understood by one of ordinary skill, each of the heuristics may be used individually or in combination to determine whether the task should be completed on the electronic device  200 , on a server, or completed partially on the device  200  and partially on the server. The heuristics may be weighted equally in the evaluation or may be weighted based on their contribution to the speed of completing the task. As well, the weightings themselves may vary as computing conditions change, for example, battery power may be weighted more heavily in shifting computation to a server if power is low or if the device  200  is not plugged into power, but may be weighted less heavily if device  200  is plugged into power or the battery level is above a predetermined threshold. For example, if network connectivity is low or unavailable the heuristic may be weighted heavily towards completing the task on device  200  without regard to other heuristics (because it impossible to complete the task on the server, either partially or entirely), whereas is network connectivity is high the heuristic may be weighted differently to take into account other factors such as battery power, memory space, cache size, etc. 
     Where the electronic device  200  includes a battery (e.g., as part of power system  262 ), one heuristic is the battery life of the electronic device  200 . Where the battery life is higher, the electronic device  200  is better able to perform the task than where the battery life is lower. A performance characteristic estimated for this heuristic is power consumption, according to some embodiments. 
     One heuristic is the availability at the electronic device  200  of high-frequency wireless networking service compliant with the IEEE 802.11x standard, commonly referred to as a “Wi-Fi® network” (trademarked by the Wi-Fi Alliance of Austin, Tex.). Where high-frequency wireless networking compliant with the IEEE 802.11x standard is not available at the electronic device  200 , the electronic device  200  is better able to perform the task than when high-frequency wireless networking compliant with the IEEE 802.11x standard is available at the electronic device  200 . Performance characteristics estimated for this heuristic are speed and power consumption, according to some embodiments. 
     One heuristic is the wireless network speed available to the electronic device  200 . According to some embodiments, the wireless network is a cellular network, and wireless network speed over a cellular network is one of 1×, 2G, 3G, 4G, and LTE® service (trademarked by the European Telecommunications Standards Institute (ETSI) of Sophia Antipolis, France). The availability of faster speeds on a portable device varies with many factors, and a portable device cannot reliably count on access to the highest speed of LTE® service. Where higher wireless network speed is not available at the electronic device  200 , the electronic device  200  is better able to perform the task than when higher wireless network speed is available at the electronic device  200 . Performance characteristics estimated for this heuristic are speed and power consumption, according to some embodiments. 
     One heuristic is available memory space, such as within memory  202 , of the electronic device  200 . Where more memory is available locally on the electronic device  200 , the electronic device  200  is better able to perform the task than when less memory is available at the electronic device  200 . Performance characteristics estimated for this heuristic are speed and relative efficiency, according to some embodiments. 
     One heuristic is processing speed of the electronic device  200 , such as with the processor(s)  220 . Where greater processing speed is available locally on the electronic device  200 , the electronic device  200  is better able to perform the task than when less processing speed is available locally on the electronic device  200 . Performance characteristics estimated for this heuristic are speed and power consumption, according to some embodiments. 
     One heuristic is the operating system of the electronic device  200 . Different operating systems may have different speeds, efficiencies, and capabilities for load shifting. Different operating systems may include different versions of the same operating system, such as the iOS® operating system (IOS is a trademark or registered trademark of Cisco in the U.S. and other countries and is used by Apple, Inc. of Cupertino, Calif. under license) used by the iPhone® mobile digital device of Apple, Inc. of Cupertino, Calif. Newer versions of the iOS® operating system are better able to shift computational loads from the electronic device  200  than older versions of the iOS® operating system, which are less able to shift computational loads from the electronic device  200 , according to some embodiments. Performance characteristics estimated for this heuristic are speed and relative efficiency, according to some embodiments. 
     One heuristic is the available cache space at the electronic device  200 . The term “cache memory” is standard in the art, and refers to memory that a processor (such as processor(s)  220 ) can access more quickly than regular memory (such as memory  202 ). The amount of available cache memory is a function of both the absolute amount of physical cache memory space available, and the amount of cache memory occupied at any given instant. Where more cache memory is available at the electronic device  200 , the electronic device  200  is better able to perform the task than when less cache memory is available locally on the electronic device  200 . 
     One heuristic is the type of electronic device  200 . The “type” of electronic device  200  refers to the particular category of hardware to which the electronic device  200  belongs, such as but not limited to a smartphone (e.g., the iPhone® mobile digital device of Apple, Inc., Cupertino, Calif.), a tablet (e.g., the iPad® mobile digital device of Apple, Inc., Cupertino, Calif.), a laptop (e.g., the MacBook Pro® computer of Apple, Inc., Cupertino, Calif.), a television interface (e.g., the Apple TV® digital media extender of Apple, Inc., Cupertino, Calif.), a watch (e.g., the Apple Watch® wrist wearable device of Apple, Inc., Cupertino, Calif.), or other device. Some types of electronic device  200  are better able to shift computational loads from the electronic device  200  than other types of electronic device  200 , which are less able to shift computational loads from the electronic device  200 , according to some embodiments. Some types of electronic device  200  have greater ability to handle computational loads than other types of electronic device  200 , according to some embodiments. Performance characteristics estimated for this heuristic are speed and relative efficiency, according to some embodiments. 
     One heuristic includes one or more privacy settings associated with the task. The user is able to adjust one or more privacy settings associated with the task, limiting the ability of the electronic device  200  to transmit user information, according to some embodiments. Where the privacy settings limit or prevent the transmission out of the electronic device  200  of user information necessary to perform the task, the electronic device  200  performs the task itself in accordance with the privacy settings, according to some embodiments. 
     One heuristic includes one or more data transmission restrictions associated with the task. In some embodiments, restrictions are associated with certain user data associated with the task. In some embodiments, these restrictions are legal in nature, where the laws in a particular jurisdiction in which the electronic device  200  is located prevent certain user data from leaving that jurisdiction. In other embodiments, these restrictions are policy restrictions of the network provider through which the electronic device  200  accesses outside networks, which prevent the transmission of certain data. In other embodiments, these restrictions are technical restrictions that prevent the transmission of certain data for technological reasons. Where data transmission restrictions are associated with the task, the electronic device  200  performs the task itself in accordance with those data transmission restrictions, according to some embodiments. 
     One heuristic includes the location of the electronic device  200 . The location of the electronic device  200  may be used as a proxy for certain network characteristics, as a proxy for data transmission restrictions, or on its own as information utilized by the DA client  102  for estimating performance characteristics. Where the electronic device  200  is in a location at which data transmission services are spotty, slow or otherwise less optimal, the electronic device  200  is better able to perform the task than when the electronic device  200  is in a location at which data transmission services are more optimal. Performance characteristics estimated for this heuristic are speed, relative efficiency, and power consumption, according to some embodiments. 
     One heuristic includes characteristics of the at least one task. The “characteristics” refer to the kind of task and to its need (or lack thereof) to access user data on the electronic device  200 . In accordance with this example, speech recognition is a task that is less likely to require access to user data on the electronic device  200 . In other examples, where the task requires access to a user&#39;s contacts that are stored locally on the electronic device  200 , the task would require access to user data on the electronic device  200 . Where the electronic device  200  requires, or is more likely to require, access to user data on the electronic device  200  in order to perform the task, the electronic device  200  is better able to perform the task than when the electronic device  200  does not require, or is less likely to require, access to user data on the electronic device  200  in order to perform the task. Performance characteristics estimated for this heuristic are speed and relative efficiency, according to some embodiments. 
     One heuristic includes user preferences associated with the task. The user may choose one or more options associated with a task that emphasize or de-emphasize speed, accuracy, or other factors, each of which may compete with one another. Where user preferences for a task are better met when the task is performed locally, the electronic device  200  is better able to perform the task than when user preferences for a task are better met when the task is performed remotely. 
     One heuristic includes utilization of strict prompts by the task. As used in this document, in relation to a task, the term “strict prompt” refers to a prompt issued by the task for which there are only a limited number of acceptable user utterances. For example, in some embodiments, the virtual assistant  700  handles disambiguation by asking a question of the user, such as “did you mean find a good place for sushi near me?” The only acceptable user utterances in response are “yes” or “no.” Anything else is ignored, or treated as a “yes” or a “no.” Where the task utilizes strict prompts, less computational power is used to handle user utterances, and the electronic device  200  is better able to perform the task than when the task does not utilize strict prompts for user interaction. Performance characteristics estimated for this heuristic are speed and relative efficiency, according to some embodiments. 
     In this example, the DA client  102  estimates the performance characteristic of speed of completion of speech recognition with the electronic device  200 , based on at least one heuristic such as the ones described above. The DA client  102  then determines whether to execute the task at the electronic device  200 . According to some embodiments, one heuristic may be dispositive. As one example, where privacy settings and/or data transmission restrictions prevent transmission from the electronic device  200  of user data or other information necessary to perform speech recognition, that task of speech recognition is performed at the electronic device  200  in order to comply with privacy settings and/or data transmission restrictions. According to other embodiments, the DA client determines whether to execute the speech recognition task at the electronic device  200  based on two or more heuristics, based on estimating at least one performance characteristic for completion of the speech recognition. Where more than one heuristic is used, the results of the heuristics are averaged, weighted, or handled in any suitable manner to perform the determining. As one example, each heuristic is assigned a binary 1 or 0 value associated with whether the task should be performed by the electronic device  200  or transmitted outside the electronic device for execution, respectively. Where the values sum to an amount over a threshold, the task is performed at the electronic device  200 . As another example, each heuristic assigns a value either to the electronic device  200  or to transmission of the task outside the electronic device  200 , and the values for each are summed; if the sum associated with the electronic device  200  is higher, the electronic device  200  performs the task and if the sum associated with transmission of the task outside the electronic device  200  is higher, the task is transmitted outside the electronic device  200 . As another example, one or more heuristics are weighted more highly than other heuristics, where such heuristics influence the selection of the location of task performance more strongly. As another example, each heuristic used in the estimating is assigned a number, and the determining averages the number. The average may be weighted or unweighted. The average number is associated with the location of task performance. 
     In the present example, the characteristics of the task to be performed—speech recognition—include computational intensiveness, mitigating toward performing the task outside the electronic device  200 . In addition, the device is a tablet, and is an older model, with less computational power. A high-frequency wireless networking service compliant with IEEE 802.11x is available at the electronic device  200 . Thus, the DA client  102  determines, based on the estimating performed on the heuristics, the task of speech recognition is performed outside the electronic device  200 . In accordance with that determination, the electronic device generates executable code for carrying out that task of speech recognition, and then transmits that code from the electronic device  200 . In response to that transmission, at a later time, information associated with execution of that executable code is received at the electronic device  200 . According to some embodiments, the electronic device  200  repeats these steps described above with regard to one or more additional tasks, where each such task is independently evaluated for execution on the electronic device  200  or outside the electronic device  200 . According to other embodiments, once the determination has been made to utilize the electronic device  200  to perform one task associated with a user request, the electronic device  200  performs all tasks associated with the user request, such that the information associated with execution of the executable code that is received at the electronic device  200  is information that fulfills the user request. When the user request is fulfilled, the electronic device  200  displays output  772  on the display  212 , according to some embodiments. Here, where the user has requested the virtual assistant  700  to “find a good sushi restaurant near me,” as shown in  FIG. 8D  the electronic device  200  displays the name, rating, distance, and address of the Sushi Shed, which fulfills the user request. 
     As another example, referring to  FIG. 8C , an electronic device  200  includes a display  212  and a microphone  213  in accordance with some embodiments. A digital assistant, as described above, is accessed by a user, who makes a request for service from a virtual assistant. In the example of  FIG. 8C , the user utters unstructured natural language user input that is acquired via the microphone  213 . The timing of the user request is under the control of the user. In this example, user input  770  is an unstructured natural language request to “email this photo of my daughter to Mom with a note that says ‘Merry Christmas!’”. The user input is converted from speech to text, and in accordance with some embodiments, the textual user input  770  is displayed on the display  212 . By displaying the textual user input  770 , in accordance with some embodiments, the user can verify that the digital assistant has received correctly the request as made. In other embodiments, such as but not limited to embodiments in which the digital assistant is operable in a hands-free mode, the textual user input  770  is not displayed. The electronic device  200  of  FIG. 8A  is a smartphone, a tablet, a laptop, or other portable device, according to some embodiments. According to other embodiments, the electronic device  200  of  FIG. 8A  is a desktop computer; a device connected to a television such as an Apple TV® digital media extender of Apple, Inc., Cupertino, Calif.; or other less-portable device that generally remains in one location. 
     The DA client  102  goes through a similar process as set forth above, of determining at least one task to perform, estimating at least one performance characteristic for completion of the at least one task with the electronic device  200 , based on at least one heuristic, and based on the estimating, determining whether to execute at least one task at the electronic device  200 . In this example, the task is query resolution. In order to resolve the query, the virtual assistant  700  needs to, among other things, determine which people “my daughter” and “Mom” refer to, and determine Mom&#39;s email address. 
     In the present example, the characteristics of the task to be performed—query resolution—require the virtual assistant  700  to utilize personal data  778  on the electronic device  200 . “Personal data” means personally-identifiable data maintained on the device rather than on the server, due to standard protocols and/or user selection of privacy settings relative to that data. Specifically, the virtual assistant  700  needs to search in personal data  778  on the electronic device  200  to determine the identity of “my daughter” and “Mom.” Such personal data  778  includes contact information, tags of photos, electronic mail messages, text messages, and other data that is stored only on the electronic device  200 , according to some embodiments. The virtual assistant  700  also needs to search the contacts stored in personal data  778  on the electronic device  200  to determine the email address of “Mom.” Because this data is present only on the phone, one of the heuristics includes privacy settings associated with the task of query resolution. In some embodiments, the user has set privacy settings to prevent contact information and photo tag information from being transmitted outside the electronic device. If so, because one or both of those actions are associated with the task, the DA client  102  utilizes the privacy setting heuristic to determine to execute the task on the electronic device  200 . Another of the heuristics includes data transmission restrictions associated with the task of query resolution. In some embodiments, the user may be in one country, and the DA server  106  may be in another country. For example, the user may be traveling outside of his or her home country. The country in which the user is located may prohibit transmittal of personal user data out of the country. If so, because one or more prohibited actions are associated with the task, the DA client  102  utilizes the data transmission heuristic to determine to execute the task on the electronic device  200 . 
     In a variant of this example, assume that neither privacy settings nor data transmission restrictions prevent the DA client  102  from transmitting information out of the electronic device  200 . However, the electronic device  200  is at a location in a national park, away from reliable network service, and the only available network is a 1× speed network. No high-frequency wireless networking service compatible with IEEE 802.11x is available. Further, the electronic device  200  is a newer smartphone with a fast processing speed. Based on these heuristics, the DA client  102  determines to execute the speech recognition task at the electronic device  200  itself. In each variant of the example, the task is executed on the electronic device. 
     According to some embodiments, the electronic device  200  repeats these steps described above with regard to one or more additional tasks, where each such task is independently evaluated for execution on the electronic device  200  or outside the electronic device  200 . According to other embodiments, once the determination has been made to utilize the electronic device  200  to perform one task associated with a user request, the electronic device  200  performs all tasks associated with the user request. When the user request is fulfilled, the electronic device  200  displays output  772  on the display  212 , according to some embodiments. Here, as shown in  FIG. 8D  the electronic device  200  displays a message that “I just sent that to your mom&#39;s default email address.” 
       FIGS. 9A-9H  are flow diagrams illustrating methods  900 ,  940 ,  980  for operating a digital assistant according to various examples. More specifically, methods  900 ,  940 ,  980  can be implemented to perform task execution with a virtual assistant. The methods  900 ,  940 ,  980  can be performed using one or more electronic devices implementing a digital assistant. In some examples, the methods  900 ,  940 ,  980  can be performed using a client-server system (e.g., system  100 ) implementing a digital assistant. The individual blocks of the methods  900 ,  940 ,  980  may be distributed in any appropriate manner among one or more computers, systems, or electronic devices. For instance, as described below, in some examples, methods  900 ,  940 ,  980  can be performed entirely on an electronic device (e.g., devices  104 ,  200 ,  400 , or  600 ). For example, the electronic device  104 ,  200 ,  400 ,  600  utilized in several examples is a smartphone. However, the methods  900 ,  940 ,  980  are not limited to use with a smartphone; the methods  900 ,  940 ,  980  may be implemented on any other suitable electronic device, such as a tablet, a desktop computer, a laptop, or a smart watch. Further, while the following discussion describes methods  900 ,  940 ,  980  as being performed by a digital assistant system (e.g., system  100  and/or digital assistant system  700 ), it should be recognized that the process or any particular part of the process is not limited to performance by any particular device, combination of devices, or implementation. The description of the process is further illustrated and exemplified by  FIGS. 8A-8E , and the description above related to those figures. 
       FIGS. 9A-9B  are a flow diagram  900  illustrating a method for executing tasks with a virtual assistant. Method  900  is performed at an electronic device  104 ,  200 ,  400 ,  600  that includes a DA client  102 , in accordance with some embodiments. The DA client  102  is part of a system  100  that includes DA server  106 , in accordance with some embodiments. However, method  900  describes client-side operation at the electronic device  104 ,  200 ,  400 ,  600 . Some operations in method  900  may be combined, the order of some operations may be changed, and some operations may be omitted. In particular, optional operations indicated with dashed-line shapes in  FIGS. 9A-9B  may be performed in any suitable order, if at all, and need not be performed in the order set forth in  FIGS. 9A-9B . 
     As described below, method  900  provides an intuitive way for executing tasks with a virtual assistant. The method reduces the cognitive burden on a user for executing tasks using a digital assistant, and improves user satisfaction with the performance of the digital assistant, thereby creating a more efficient human-machine interface. For battery-operated computing devices, enabling improved execution of tasks with a digital assistant more accurately and more efficiently conserves power and increases the time between battery charges. 
     At the beginning of method  900 , the digital assistant receives  902  user input for service from a virtual assistant. The user input includes unstructured natural language speech including one or more words, in some embodiments. Where the electronic device  104 ,  200 ,  400 ,  600  includes or is associated with a microphone  213 , that user input may be received through the microphone  213 . The user input may also be referred to as an audio input or audio stream. In some embodiments, the stream of audio can be received as raw sound waves, as an audio file, or in the form of a representative audio signal (analog or digital). In other embodiments, the audio stream can be received at a remote system, such as a server component of a digital assistant. The audio stream can include user speech, such as a spoken user request. In other embodiments, the user input is received in textual form instead of as speech. In other embodiments, the user input is received through touch-sensitive display system  212  as a tap, touch, or other gesture. 
     The DA client  102  at the electronic device  104 ,  200 ,  400 ,  600  determines  904  at least one task to perform in response to the user request, in accordance with some embodiments. As set forth above with regard to  FIGS. 8A-8E , in accordance with some embodiments the tasks include one or more of context resolution, speech recognition, automatic speech recognition, domain classification, natural language parsing, query resolution, natural language synthesis, user interface resolution, and text-to-speech conversion. 
     According to some embodiments, after determining at least one task to perform in response to the user request, the DA client  102  estimates  906  at least one performance characteristic for completion of the at least one task with the electronic device  104 ,  200 ,  400 ,  600 , based on at least one heuristic. As set forth above with regard to  FIGS. 8A-8E , in accordance with some embodiments, the performance characteristics are one or more of speed of task performance, relative efficiency of task performance, power consumption of task performance, and/or other relevant performance metrics. In accordance with some embodiments, a number of heuristics are set forth and described above with regard to  FIGS. 8A-8E . 
     According to some embodiments, either immediately after block  906  or at a later time after block  906 , the DA client  102  repeats block  904 , as illustrated by the dashed line from block  906  to block  904 . In this way, the DA client  102  individually estimates, for two or more discrete tasks, at least one performance characteristic for completion of each task with the electronic device  104 ,  200 ,  400 ,  600 , based on at least one heuristic. 
     The digital assistant determines  908 , based on the estimate of block  906 , whether to execute the at least one task at the electronic device  104 ,  200 ,  400 ,  600 . The digital assistant makes this determination in any suitable manner. As set forth above, according to some embodiments, one heuristic (such as privacy settings or data transmission restrictions) may be dispositive. According to other embodiments, the DA client determines whether to execute the speech recognition task at the electronic device  200  based on two or more heuristics, based on estimating at least one performance characteristic for completion of the speech recognition. Where more than one heuristic is used, the results of the heuristics are averaged, weighted, or handled in any suitable manner to perform the determining. Examples of the determination  908 , based on the estimate of block  906 , are provided above relative to  FIGS. 8A-8E . 
     In accordance with a determination to execute at least one task at the electronic device  104 ,  200 ,  400 ,  600 , the DA client  102  causes  910  execution of at least one task at the electronic device  104 ,  200 ,  400 ,  600 . The execution is performed at processors  220 , in some embodiments. In other embodiments, the execution is performed at any suitable hardware element or elements at the electronic device  104 ,  200 ,  400 ,  600 . In some embodiments, in block  910 , the DA client  102  generates, or causes another component of the electronic device  104 ,  200 ,  400 ,  600  to generate, executable code that executes the at least one task at the electronic device  104 ,  200 ,  400 ,  600 . The executable code is written in JavaScript language, according to some embodiments, although any other suitable language can be used. The executable code is generated based on the particular task to be performed. The executable code, according to some embodiments, includes code that determines whether all information necessary for task execution is available to the virtual assistant, obtains or causes to be obtained any missing information necessary for task execution, and executes the task. 
     Optionally, the causing execution of block  910  is performed  912  using personal data  778  on the electronic device  104 ,  200 ,  400 ,  600 , where personal data  778  is retained on the electronic device  104 ,  200 ,  400 ,  600 . As described above relative to  FIGS. 8A-8E , privacy settings, data transmission restrictions, and/or other privacy-related and data protection heuristics can result in the determination in block  908  to cause execution of at least one task at the electronic device  104 ,  200 ,  400 ,  600 . In this way, personal data  778  is retained on the electronic device  104 ,  200 ,  400 ,  600  and is not transmitted outside the device, even to the DA server  106  component of the virtual assistant. Such personal data  778  is thus not vulnerable to interception en route to the DA server  106  or other location outside the electronic device  104 ,  200 ,  400 ,  600 , and by retaining the personal data  778  on the electronic device  104 ,  200 ,  400 ,  600 , such data is not vulnerable to hackers who may penetrate a server or other device remote from the electronic device  104 ,  200 ,  400 ,  600 . 
     According to some embodiments, the causing execution of block  910  is performed by storing  914  executable code at the electronic device  104 ,  200 ,  400 ,  600 , and causing  916  execution of the stored executable code at the electronic device  104 ,  200 ,  400 ,  600 . Storing at the electronic device  104 ,  200 ,  400 ,  600  executable code associated with task execution consumes more memory space than generating the executable code “on the fly,” as described above. However, in some embodiments, it is faster to locate and execute stored executable code than to generate executable code and cause its execution in block  910 . 
     Optionally, according to some embodiments, after causing  910  execution of at least one task at the electronic device  104 ,  200 ,  400 ,  600 , the DA client  102  or other component of the electronic device  104 ,  200 ,  400 ,  600  transmits  918 , from the electronic device  104 ,  200 ,  400 ,  600 , the results of causing execution in block  910 . In some embodiments, the results of causing execution in block  910  are transmitted to the DA server  106  for further processing, and/or for use as input to a process to be executed at the DA server  106 . In other embodiments, the results of causing execution in block  910  are transmitted in block  918  in order to fulfill the user request. Such transmissions include, but are not limited to, sending an email (as described above with regard to  FIGS. 8C-8D ), message, or other communication. 
     Returning to block  908 , in accordance with a determination to execute at least one task outside the electronic device  104 ,  200 ,  400 ,  600 , the DA client  102  generates  920  executable code for carrying out the at least one task, in accordance with some embodiments. The generating  920  is performed in substantially the same manner as described above with regard to generating executable code in some embodiments of block  910 . In some embodiments, the executable code is configured to interface with another portion of the virtual assistant  700  through text representations of commands, rather than accessing the primitives of the virtual assistant directly. Those text commands interact with an API of the virtual assistant  700 . In this way, the code generated by the DA client  102  poses a low and manageable security risk, and a path for infection by malware is closed. In accordance with other embodiments, another component of the electronic device  104 ,  200 ,  400 ,  600 , instead of or in coordination with the DA client  102 , generates the executable code for carrying out the at least one task. 
     After generating the executable code, the executable code is transmitted  922  from the electronic device  104 ,  200 ,  400 ,  600 . In accordance with some embodiments, the DA client  102  initiates the transmission. In accordance with other embodiments, another component of the electronic device  104 ,  200 ,  400 ,  600 , instead of or in coordination with the DA client  102 , transmits from the electronic device  104 ,  200 ,  400 ,  600  executable code for carrying out the at least one task. In some embodiments, optionally the executable code is transmitted  924  from the electronic device  104 ,  200 ,  400 ,  600  to the DA server  106 , where the virtual assistant  700  is divided between the electronic device  104 ,  200 ,  400 ,  600  and a remote server. As described above with regard to  FIGS. 8A-8E  and examples illustrating those figures, based on one or more heuristics, executing a task at a server (such as by executing executable code transmitted from the electronic device  104 ,  200 ,  400 ,  600  to the server) and returning the results of that task to the electronic device  104 ,  200 ,  400 ,  600  can result in better performance characteristics than executing the code on the electronic device  104 ,  200 ,  400 ,  600  itself. 
     Optionally, according to some embodiments, the executable code is transmitted  926  from the electronic device  104 ,  200 ,  400 ,  600  to a second electronic device, rather than the DA server. For example, the executable code may be transmitted from a watch, such as the Apple Watch® wrist wearable device of Apple, Inc., Cupertino, Calif., to a smartphone, such as the iPhone® mobile digital device of Apple, Inc. of Cupertino, Calif. In this way, computational tasks can be offloaded from a watch to a more computationally powerful device, over a local network, without the need to access a more distant server across a longer network. The electronic device  104 ,  200 ,  400 ,  600  is connected to the second electronic device over a local network, such as a Bluetooth® network or high-frequency wireless networking service compliant with IEEE 802.11x, in some embodiments. 
     Optionally, according to some embodiments, after transmitting  926  the executable code to a second electronic device, the method fulfills  928  the user request at the second electronic device. For example, the electronic device  104 ,  200 ,  400 ,  600  is an iPhone® mobile digital device of Apple, Inc. of Cupertino, Calif., and the second electronic device is an Apple TV® digital media extender of Apple, Inc., Cupertino, Calif. The iPhone® mobile digital device transmits executable code to the Apple TV® digital media extender, which in response plays a movie responsive to the user request in order to fulfill the user request. In this way, the electronic device  104 ,  200 ,  400 ,  600  can take advantage of a variety of other devices to which the electronic device  104 ,  200 ,  400 ,  600  is connected in order to improve computing performance, as well as take advantage of a variety of other devices to fulfill a user request in the most effective manner. For example, the user may have requested playback of a movie from the iPhone® mobile digital device, but may be in the same room as a large television connected to an Apple TV® digital media extender. The electronic device  104 ,  200 ,  400 ,  600  (here the iPhone® mobile digital device), in some embodiments, determines that the second electronic device (here, the Apple TV® digital media extender) will provide a better experience for the user, and thereby uses block  928  to fulfill the user request at the second electronic device. 
     Optionally, according to some embodiments, after transmitting  960  the executable code from the electronic device  104 ,  200 ,  400 ,  600 , the DA client  102  receives information associated with execution of the executable code. In this way, tasks executed remotely from the electronic device  104 ,  200 ,  400 ,  600  return a result of that task execution to the electronic device  104 ,  200 ,  400 ,  600 . 
     In accordance with some embodiments,  FIG. 10A  shows an exemplary functional block diagram of an electronic device  1100  configured in accordance with the principles of the various described embodiments. In accordance with some embodiments, the functional blocks of electronic device  1100  are configured to perform the techniques described above. The functional blocks of the device  1100  are, optionally, implemented by hardware, software, or a combination of hardware and software to carry out the principles of the various described examples. It is understood by persons of skill in the art that the functional blocks described in  FIG. 10A  are, optionally, combined or separated into sub-blocks to implement the principles of the various described examples. Therefore, the description herein optionally supports any possible combination or separation or further definition of the functional blocks described herein. 
     As shown in  FIG. 10A , an electronic device  1100  optionally includes a display unit  1102  configured to display a graphic user interface; optionally, a touch-sensitive surface unit  1104  configured to receive contacts, a microphone unit  1106  configured to receive audio signals, and a processing unit  1108  optionally coupled to the display unit  1102 , the touch-sensitive surface unit  1004  and/or the microphone unit  1006 . In some embodiments, the processing unit  1108  includes a transmitting unit  1110 , receiving unit  1112 , a determining unit  1114 , an estimating unit  1116 , a causing unit  1118 , a generating unit  1214 , and optionally a storing unit  1122 . 
     According to some embodiments, a processing unit is configured to receive (e.g., with receiving unit  1112 ) a user request for a service from a virtual assistant; determine (e.g., with determining unit  1114 ) at least one task to perform in response to the user request; estimate (e.g., with estimating unit  1116 ) at least one performance characteristic for completion of the at least one task with the electronic device, based on at least one heuristic; based on the estimate, determine (e.g., with determining unit  1114 ) whether to execute the at least one task at the electronic device; in accordance with a determination to execute the at least one task at the electronic device, cause (e.g., with causing unit  1118 ) the execution of the at least one task at the electronic device; in accordance with a determination to execute the at least one task outside the electronic device, generate (e.g., with the generating unit  1120 ) executable code for carrying out the least one task; and transmit (e.g., with the transmitting unit  1110 ) the executable code from the electronic device. 
     In some embodiments, where the electronic device  1100  includes a battery, the at least one heuristic includes the battery life of the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes availability at the electronic device  1100  of high-frequency wireless networking service compliant with the IEEE 802.11x standard. 
     In some embodiments, the at least one heuristic includes network speed available to the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes available memory space of the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes processing speed of the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes the operating system of the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes available cache space at the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes the type of electronic device  1100 . 
     In some embodiments, the at least one heuristic includes privacy settings associated with the at least one task. 
     In some embodiments, the at least one heuristic includes data transmission restrictions associated with the at least one task. 
     In some embodiments, the at least one heuristic includes location of the electronic device  1100 . 
     In some embodiments, the at least one heuristic includes the characteristics of the at least one task. 
     In some embodiments, the at least one heuristic includes user preferences associated with the task. 
     In some embodiments, the at least one heuristic includes utilization of strict prompts by the task. 
     In some embodiments, the at least one task includes at least one of: context resolution; speech recognition; automatic speech recognition; domain classification; natural language parsing; query resolution; natural language synthesis; user interface resolution; and text-to-speech conversion. 
     In some embodiments, in response to the transmission of executable code from the electronic device  1100 , the processing unit  1108  is configured to receive (e.g., with receiving unit  1112 ) information associated with execution of the executable code. 
     In some embodiments, the processing unit  1108  is configured to cause (e.g., with causing unit  1118 ) the execution to be performed using user data on the electronic device, wherein user data is retained on the electronic device  1100 . 
     In some embodiments, the processing unit  1108  is configured to cause (e.g., with causing unit  1118 ) the execution to be performed in a sandbox at the electronic device  1100 . 
     In some embodiments, after the cause of the execution, the processing unit  1108  is configured to transmit (e.g., with the transmitting unit  1110 ) the results of the cause of the execution from the electronic device  1100 . 
     In some embodiments, the processing unit  1108  is configured to estimate (e.g., with the estimating unit  1116 ) and determine (e.g., with the determining unit  1114 ) for at least two discrete tasks. 
     In some embodiments, the processing unit  1108  further comprises a storing unit  1122 ; wherein the processing unit  1108  is further configured to cause (e.g., with causing unit  1118 ) the execution to: store (e.g., with storing unit  1122 ) executable code on the electronic device; and cause (e.g., with causing unit  1118 ) the execution of the stored code on the electronic device  1100 . 
     In some embodiments, the user request is in unstructured natural language format. 
     In some embodiments, one performance characteristic is an estimated duration to complete the at least one task. 
     In some embodiments, the virtual assistant is distributed between the electronic device  1100  and the server, and the processing unit  1108  is configured to transmit (e.g., with the transmitting unit  1110 ) the executable code to the server. 
     In some embodiments, the processing unit  1108  is configured to transmit (e.g., with the transmitting unit  1110 ) the executable code to a second electronic device. 
     In some embodiments, the second electronic device is connected to the electronic device over a local network. 
     The operations described above with reference to  FIGS. 9A-9B  are, optionally, implemented by components depicted in  FIGS. 1A-7C ,  FIG. 8E , and/or  FIG. 10 . It would be clear to a person having ordinary skill in the art how processes can be implemented based on the components depicted in  FIGS. 1A-7C ,  FIG. 8E , and/or  FIG. 10 . 
       FIGS. 9C-9D  are a flow diagram  940  illustrating a method for executing tasks with a virtual assistant. Method  900  is performed at an electronic device  108  that includes a DA server  106  in accordance with some embodiments. The DA server  106  is part of a system  100  that includes DA client  102 , in accordance with some embodiments. However, method  940  describes server-side operation at the server  108 . Some operations in method  940  may be combined, the order of some operations may be changed, and some operations may be omitted. In particular, optional operations indicated with dashed-line shapes in  FIGS. 9C-9D  may be performed in any suitable order, if at all, and need not be performed in the order set forth in  FIGS. 9C-9D . 
     As described below, method  940  provides an intuitive way for executing tasks with a virtual assistant. The method reduces the cognitive burden on a user for executing tasks using a digital assistant, and improves user satisfaction with the performance of the digital assistant, thereby creating a more efficient human-machine interface. 
     At the beginning of method  940 , the digital assistant receives  942  user input for service from a virtual assistant. In some embodiments, an audio stream the audio stream is received at the DA server  106  from the electronic device  104 ,  200 ,  400 ,  600 . The audio stream can include user speech, such as a spoken user request. In other embodiments, the user input is received in textual form instead of as speech. In other embodiments, the user request is received by the DA server  106  at the server system  108  in any suitable manner. 
     The DA server  106  determines  944  at least one task to perform in response to the user request, in accordance with some embodiments. As set forth above with regard to  FIGS. 8A-8E , in accordance with some embodiments the tasks include one or more of context resolution, speech recognition, automatic speech recognition, domain classification, natural language parsing, query resolution, natural language synthesis, user interface resolution, and text-to-speech conversion. 
     After determining at least one task to perform in response to the user request, the DA server  106  estimates  946  at least one performance characteristic for completion of the at least one task with the server  108 , based on at least one heuristic. As set forth above with regard to  FIGS. 8A-8E , in accordance with some embodiments, the performance characteristics are one or more of speed of task performance, relative efficiency of task performance, power consumption of task performance, and/or other relevant performance metrics. In accordance with some embodiments, a number of heuristics are set forth and described above with regard to  FIGS. 8A-8E . In addition, in accordance with other embodiments, one or more other heuristics may be used. 
     One heuristic is the network speed available to the server  108 . Wireless network heuristics are described above. Similarly, wired network service is classified into groups based on network speed. Where higher network speed is not available at the server  108 , the server  108  is better able to perform the task than when higher network speed is available at the server  108 . Performance characteristics estimated for this heuristic include speed and power consumption, according to some embodiments. While power consumption is not critical to a server  108  in terms of battery life, it is generally desired to reduce the overall power consumption of a server  108  for economic and environmental reasons. 
     One heuristic is network latency between the server  108  and the electronic device  104 ,  200 ,  400 ,  600 . This latency also may be expressed between the DA server  106  and the DA client  102 . Network latency refers to the time it takes for a packet of data to get from one designated point to another. Where higher network latency is experienced at the server  108 , the server  108  is better able to perform the task than when lower network latency is experienced at the server  108 . Performance characteristics estimated for this heuristic include speed, according to some embodiments. 
     One heuristic is load at the server  108 . Load refers to the demand for services at the server  108 , and is higher when requests for task performance arrive at a higher rate and/or are associated with tasks bearing a higher computational load. Where lesser load is experienced at the server  108 , the server  108  is better able to perform the task than when higher load is experienced at the server  108 . Performance characteristics estimated for this heuristic include speed and power consumption, according to some embodiments. 
     One heuristic is capacity at the server  108 . Capacity refers to the ability of the server  108  to perform additional tasks over and above the tasks it is currently performing, and is higher when requests for task performance arrive at a lower rate and/or are associated with tasks bearing a lower computational load. Capacity may be hard (a fixed ceiling on the tasks that can be performed) or soft (a moveable ceiling that can be adjusted based on load). Where the server  108  has a higher capacity, the server  108  is better able to perform the task than when the server  108  has a lower capacity. Performance characteristics estimated for this heuristic include speed and power consumption, according to some embodiments. 
     One heuristic is status of the server  108 . Status refers to the operational status of the server  108 . The server  108  may be down for maintenance, or may have crashed, such that its status is down. The server  108  may be operational fully, such that its status is up. The server  108  may be partly operational, such that its status is partially up. Where the server  108  is fully operational (“up”), the server  108  is better able to perform the task than when the server  108  is partially up or is down. When the server  108  is down, it is unable to perform any tasks. Performance characteristics estimated for this heuristic include speed, according to some embodiments. 
     One heuristic is traffic volume at the server  108 . Traffic volume refers to the number of requests reaching the server  108 , independent of the size of the requests, the nature of the requests, or the computational power needed to fulfill the requests. Where the server  108  is experiencing less traffic volume, the server  108  is better able to perform the task than when the server  108  is experiencing higher traffic volume. Performance characteristics estimated for this heuristic include speed, according to some embodiments. 
     One heuristic is data connection characteristics between the server  108  and the electronic device  104 ,  200 ,  400 ,  600 . Connection characteristics include quality of service (QoS), noise/drop-offs of the connection, packet loss rates, and any other characteristics of the data connection between the server  108  and the electronic device  104 ,  200 ,  400 ,  600 . Where worse connection characteristics are experienced at the server  108 , the server  108  is better able to perform the task than when better connection characteristics are experienced at the server  108 . Performance characteristics estimated for this heuristic include speed, according to some embodiments. 
     One heuristic is connection characteristics between the server  108  and a service provider. In order to fulfill a task, the server  108  connects to an external service provider to obtain information or perform task fulfillment, according to some embodiments. Where worse connection characteristics are experienced at the server  108 , the server  108  is better able to perform the task than when better connection characteristics are experienced at the server  108 . Performance characteristics estimated for this heuristic include speed, according to some embodiments. 
     Either immediately after block  946  or at a later time after block  946 , the DA server  106  repeats block  944 , as illustrated by the dashed line from block  946  to block  944 . In this way, the DA server  106  individually estimates, for two or more discrete tasks, at least one performance characteristic for completion of each task with the server  108 , based on at least one heuristic. 
     The digital assistant determines  948 , based on the estimate of block  946 , whether to execute the at least one task at the server  108 . The digital assistant makes this determination in any suitable manner. As set forth above, according to some embodiments, one heuristic (such as privacy settings or data transmission restrictions) may be dispositive. According to other embodiments, the DA server  106  determines whether to execute the speech recognition task at the server  108  based on two or more heuristics, based on estimating at least one performance characteristic for completion of the speech recognition. Where more than one heuristic is used, the results of the heuristics are averaged, weighted, or handled in any suitable manner to perform the determining. Examples of the determination  948 , based on the estimate of block  946 , are provided above relative to  FIGS. 8A-8E . 
     In accordance with a determination to execute at least one task at the server  108 , the DA server  106  causes  950  execution of at least one task at the server  108 . The execution is performed at processing modules  114 , in some embodiments. In other embodiments, the execution is performed at any suitable hardware element or elements at the server  108 . In some embodiments, in block  950 , the DA server  106  generates, or causes another component of the server  108  to generate, executable code that executes the at least one task at the server  108 . The executable code is written in JavaScript language, according to some embodiments, although any other suitable language can be used. The executable code is generated based on the particular task to be performed. The executable code, according to some embodiments, includes code that determines whether all information necessary for task execution is available to the virtual assistant, obtains or causes to be obtained any missing information necessary for task execution, and executes the task. 
     The causing execution of block  950  is performed by storing  952  executable code at the server  108 , and causing  954  execution of the stored executable code at the server  108 . Storing at the server  108  executable code associated with task execution consumes more memory space than generating the executable code “on the fly,” as described above. However, in some embodiments, it is faster to locate and execute stored executable code than to generate executable code and cause its execution in block  950 . 
     Optionally, according to some embodiments, after causing  950  execution of at least one task at the server  108 , the DA server  106  or other component of the server  108  transmits  956 , from the server  108 , the results of causing execution in block  950 . In some embodiments, the results of causing execution in block  950  are transmitted to the DA client  102  for further processing, and/or for use as input to a process to be executed at the DA client  102 . In other embodiments, the results of causing execution in block  950  are transmitted in block  956  in order to fulfill the user request. Such transmissions include, but are not limited to, sending an email (as described above with regard to  FIGS. 8C-8D ), message, or other communication. 
     Returning to block  908 , in accordance with a determination to execute at least one task outside the server  108 , the DA server  106  generates  958  executable code for carrying out the at least one task, in accordance with some embodiments. The generating  958  is performed in substantially the same manner as described above with regard to generating executable code in some embodiments of block  950 . In some embodiments, the executable code is configured to interface with another portion of the virtual assistant  700  through text representations of commands, rather than accessing the primitives of the virtual assistant directly. Those text commands interact with an API of the virtual assistant  700 . In this way, the code generated by the DA server  106  poses a low and manageable security risk, and a path for infection by malware is closed. In accordance with other embodiments, another component of the server  106 , instead of or in coordination with the DA server  106 , generates the executable code for carrying out the at least one task. 
     After generating the executable code, the executable code is transmitted  960  from the server  108 . In accordance with some embodiments, the DA server  102  initiates the transmission. In accordance with other embodiments, another component of the server  108 , instead of or in coordination with the DA server  106 , transmits from the server  108  executable code for carrying out the at least one task. In some embodiments, optionally the executable code is transmitted  962  from the server  108  to the DA client  102 , where the virtual assistant  700  is divided between the server  108  and a remote electronic device  104 ,  200 ,  400 ,  600 . As described above with regard to  FIGS. 8A-8E  and examples illustrating those figures, based on one or more heuristics, executing a task at a the electronic device  104 ,  200 ,  400 ,  600  (such as by executing executable code transmitted from the server  108  to the electronic device) and returning the results of that task to the server  108  can result in better performance characteristics than executing the code on the server  108  itself. 
     Optionally, according to some embodiments, the executable code is transmitted  964  from the server  108  to a second electronic device, rather than the DA server. For example, the executable code may be transmitted from the server to an Apple TV® digital media extender of Apple, Inc., Cupertino, Calif., where the original user request was made from a smartphone, such as the iPhone® mobile digital device of Apple, Inc. of Cupertino, Calif. In this way, computational tasks can be offloaded to the most appropriate device, or the device with the best capability, for those tasks. The server  108  is connected to the second electronic device over any suitable wired or wireless network. 
     Optionally, according to some embodiments, after transmitting  964  the executable code to a second electronic device, the method fulfills  966  the user request at the second electronic device. As in the example above, the server  108  transmits executable code to the Apple TV® digital media extender, which in response plays a movie responsive to the user request in order to fulfill the user request. In this way, the server  108  can take advantage of a variety of other devices to which the electronic device  104 ,  200 ,  400 ,  600  or the server  108  itself is connected in order to improve computing performance, as well as take advantage of a variety of other devices to fulfill a user request in the most effective manner. For example, the user may have requested playback of a movie from the iPhone® mobile digital device, but may be in the same room as a large television connected to an Apple TV® digital media extender. The server  108 , in some embodiments, determines that the second electronic device (here, the Apple TV® digital media extender) will provide a better experience for the user, and thereby uses block  966  to fulfill the user request at the second electronic device. 
     Optionally, according to some embodiments, after transmitting  960  the executable code from the server  108 , the DA server  106  receives information associated with execution of the executable code. In this way, tasks executed remotely from the server  108  return a result of that task execution to the server  108 . 
       FIG. 10B  shows an exemplary functional block diagram of an electronic device  1200  configured in accordance with the principles of the various described embodiments. In accordance with some embodiments, the functional blocks of electronic device  1200  are configured to perform the techniques described above. The functional blocks of the device  1200  are, optionally, implemented by hardware, software, or a combination of hardware and software to carry out the principles of the various described examples. It is understood by persons of skill in the art that the functional blocks described in  FIG. 10B  are, optionally, combined or separated into sub-blocks to implement the principles of the various described examples. Therefore, the description herein optionally supports any possible combination or separation or further definition of the functional blocks described herein. 
     As shown in  FIG. 10B , a server  1200  includes a processing unit  1202 . In some embodiments, the processing unit  1202  includes a transmitting unit  1204 , receiving unit  1206 , a determining unit  1208 , an estimating unit  1210 , a causing unit  1212 , a generating unit  1214 , and optionally a storing unit  1216 . 
     According to some embodiments, a processing unit  1202  is configured to receive (e.g., with receiving unit  1206 ) a user request for a service from a virtual assistant; determine (e.g., with determining unit  1208 ) at least one task to perform in response to the user request; estimate (e.g., with estimating unit  1210 ) at least one performance characteristic for completion of the at least one task with the server, based on at least one heuristic; based on the estimate, determine (e.g., with determining unit  1208 ) whether to execute the at least one task at the server; in accordance with a determination to execute the at least one task at the server, cause (e.g., with causing unit  1212 ) the execution of the at least one task at the server; in accordance with a determination to execute the at least one task outside the server, generate (e.g., with the generating unit  1214 ) executable code for carrying out the least one task; and transmit (e.g., with the transmitting unit  1204 ) the executable code from the server. 
     In some embodiments, the at least one heuristic includes network latency between the server  1200  and an electronic device. 
     In some embodiments, the at least one heuristic includes network speed available to the server  1200 . 
     In some embodiments, the at least one heuristic includes load at the server  1200 . 
     In some embodiments, the at least one heuristic includes available capacity at the server  1200 . 
     In some embodiments, the at least one heuristic includes status of the server  1200 . 
     In some embodiments, the at least one heuristic includes privacy settings associated with the at least one task. 
     In some embodiments, the at least one heuristic includes data transmission restrictions associated with the at least one task. 
     In some embodiments, the at least one heuristic includes the characteristics of the at least one task. 
     In some embodiments, the at least one heuristic includes traffic volume at the server  1200 . 
     In some embodiments, the at least one heuristic includes user preferences associated with the task. 
     In some embodiments, the at least one heuristic includes characteristics of the task. 
     In some embodiments, the at least one heuristic includes characteristics of a connection from the server  1200  to a service provider. 
     In some embodiments, in response to the transmitting, the processing unit  1202  is configured to receive (e.g., with receiving unit  1206 ) information associated with execution of the executable code. 
     In some embodiments, the processing unit  1202  is further configured to, after the cause (e.g., with causing unit  1212 ) of the execution: transmit (e.g., with transmitting unit  1204 ) the results of the cause of the execution from the server  1200 . 
     In some embodiments, the processing unit  1202  is configured to estimate (e.g., with estimating unit  1210 ) and determine (e.g., with the determining unit  1208 ) for at least two discrete tasks. 
     In some embodiments, the processing unit  1202  further includes a storing unit  1216 ; wherein the processing unit  1202  is further configured to cause (e.g., with causing unit  1212 ) the execution to: store (e.g., with storing unit  1216 ) executable code on the server  1200 ; and cause (e.g., with causing unit  1212 ) the execution of the stored code on the server  1200 . 
     In some embodiments, the virtual assistant is distributed between the server  1200  and an electronic device, and wherein the processing unit  1202  is configured to transmit (e.g., with transmitting unit  1204 ) the executable code to the electronic device. 
     In some embodiments, the processing unit  1202  is configured to transmit (e.g., with transmitting unit  1204 ) the executable code to a second electronic device. 
     The operations described above with reference to  FIGS. 9C-9D  are, optionally, implemented by components depicted in  FIGS. 1A-7C ,  FIG. 8E , and/or  FIG. 10 . It would be clear to a person having ordinary skill in the art how processes can be implemented based on the components depicted in  FIGS. 1A-7C ,  FIG. 8E , and/or  FIG. 10 . 
       FIGS. 9E-9H  are a flow diagram  980  illustrating a method for executing tasks with a virtual assistant distributed between a DA client  102  located at an electronic device  104 ,  200 ,  400 ,  600  and a DA server  106  located at a server  108 . Method  980  is performed at both the electronic device  104 ,  200 ,  400 ,  600  and the server  108 . Some operations in method  980  may be combined, the order of some operations may be changed, and some operations may be omitted. In particular, optional operations indicated with dashed-line shapes in  FIGS. 9E-9H  may be performed in any suitable order, if at all, and need not be performed in the order set forth in  FIGS. 9E-9H . Where an action is described as being performed by the DA client  102 , that action can be performed instead by the DA server  106  unless expressly noted to the contrary, because both are part of the assistant  100 . 
     As described below, method  980  provides an intuitive way for executing tasks with a virtual assistant. The method reduces the cognitive burden on a user for executing tasks using a digital assistant, and improves user satisfaction with the performance of the digital assistant, thereby creating a more efficient human-machine interface. For battery-operated computing devices, enabling improved execution of tasks with a digital assistant more accurately and more efficiently conserves power and increases the time between battery charges. 
     At the beginning of method  980 , the digital assistant receives  982  user input for service from a virtual assistant. The user input includes unstructured natural language speech including one or more words, in some embodiments. Referring also to  FIGS. 8A and 8C , where the electronic device  104 ,  200 ,  400 ,  600  includes or is associated with a microphone  213 , that user input may be received through the microphone  213 . The user input may also be referred to as an audio input or audio stream. In some embodiments, the stream of audio can be received as raw sound waves, as an audio file, or in the form of a representative audio signal (analog or digital). In other embodiments, the audio stream can be received at a remote system, such as a server component of a digital assistant. The audio stream can include user speech, such as a spoken user request. In other embodiments, the user input is received in textual form instead of as speech. In other embodiments, the user input is received through touch-sensitive display system  212  as a tap, touch, or other gesture. 
     The DA client  102  at the electronic device  104 ,  200 ,  400 ,  600  determines  984  at least one task to perform in response to the user request, in accordance with some embodiments. As set forth above with regard to  FIGS. 8A-8E , in accordance with some embodiments the tasks include one or more of context resolution, speech recognition, automatic speech recognition, domain classification, natural language parsing, query resolution, natural language synthesis, user interface resolution, and text-to-speech conversion. 
     According to some embodiments, after determining at least one task to perform in response to the user request, the DA client  102  estimates  986  at least one performance characteristic for completion of the at least one task with the electronic device  104 ,  200 ,  400 ,  600 , based on at least one heuristic. As set forth above with regard to  FIGS. 8A-8E , in accordance with some embodiments, the performance characteristics are one or more of speed of task performance, relative efficiency of task performance, power consumption of task performance, and/or other relevant performance metrics. In accordance with some embodiments, a number of heuristics are set forth and described above with regard to  FIGS. 8A-8E . With regard to the method  980 , the heuristics described above relating to communications from the electronic device  104 ,  200 ,  400 ,  600  or the server  108  relate here to communications between the electronic device  104 ,  200 ,  400 ,  600  and the server  108 . 
     Optionally, as part of the estimating  986 , the DA client  102  determines  988  a speed with which each of the electronic device  104 ,  200 ,  400 ,  600  and the server  108  is able to execute the at least one task. The DA client  102  communicates with the DA server  106  as part of the determining, according to some embodiments. In other embodiments, the DA client  102  makes assumptions about the speed with which the server  108  is able to execute the at least one task, such as by basing an assumption upon recent interaction with the DA server  106 . Optionally, as part of the estimating  986 , after determining  988  the speeds, the DA client  102  compares  990  the speed with which the electronic device  104 ,  200 ,  400 ,  600  is able to execute at least one task with the speed with which the server  10  is able to execute at least one task. Optionally, as part of the comparing  990  speeds, the DA client  102  determines  992  the difference between the speeds, and compares  994  that difference to a threshold. 
     According to some embodiments, either immediately after block  986  or at a later time after block  986 , the DA client  102  repeats block  984 , as illustrated by the dashed line from block  986  to block  984 . In this way, the DA client  102  individually estimates, for two or more discrete tasks, at least one performance characteristic for completion of each task with the electronic device  104 ,  200 ,  400 ,  600 , based on at least one heuristic. 
     The digital assistant determines  996 , based on the estimate of block  986 , whether to execute the at least one task at the electronic device  104 ,  200 ,  400 ,  600  or at the server  108 . The digital assistant makes this determination in any suitable manner. As set forth above, according to some embodiments, one heuristic (such as privacy settings or data transmission restrictions) may be dispositive. According to other embodiments, the DA client  102  determines whether to execute the speech recognition task at the electronic device  104 ,  200 ,  400 ,  600  or at the server  108  based on two or more heuristics, based on estimating at least one performance characteristic for completion of the speech recognition. Where more than one heuristic is used, the results of the heuristics are averaged, weighted, or handled in any suitable manner to perform the determining. Examples of the determination  996 , based on the estimate of block  986 , are provided above relative to  FIGS. 8A-8E . Where the estimating  986  also includes comparing  990  speeds and comparing  994  the difference in speed to a threshold, as described above, in response to determining that the difference is greater than the threshold, the DA client  102  determines  996  that the faster of the electronic device  104 ,  200 ,  400 ,  600  and the server  108  performs the task. If the difference is under the threshold, the process moves to block  1014 , as described in greater detail below. 
     In accordance with a determination  996  to execute at least one task at the electronic device  104 ,  200 ,  400 ,  600 , the DA client  102  causes  998  execution of at least one task at the electronic device  104 ,  200 ,  400 ,  600 . Where blocks  990 - 994  have been performed, the determination is based on the electronic device  104 ,  200 ,  400 ,  600  being faster than the server  108  to perform the task, with a difference in speed over a threshold. The execution is performed at processors  220 , in some embodiments. In other embodiments, the execution is performed at any suitable hardware element or elements at the electronic device  104 ,  200 ,  400 ,  600 . In some embodiments, in block  998 , the DA client  102  generates, or causes another component of the electronic device  104 ,  200 ,  400 ,  600  to generate, executable code that executes the at least one task at the electronic device  104 ,  200 ,  400 ,  600 . The executable code is written in JavaScript language, according to some embodiments, although any other suitable language can be used. The executable code is generated based on the particular task to be performed. The executable code, according to some embodiments, includes code that determines whether all information necessary for task execution is available to the virtual assistant, obtains or causes to be obtained any missing information necessary for task execution, and executes the task. 
     According to some embodiments, in the course of fulfilling a user request for service by performing a plurality of tasks, the DA client  102  and the DA server  106  will pass task execution to the other two or more times, without user intervention. Such passing of tasks back and forth is a result of iteratively performing blocks  984  and  986  after each task is complete, or after each of a subset of tasks is complete. As set forth in greater detail below, execution of a task by the DA client  102  and/or DA server  106  code is deferred in some situations, according to some embodiments. As one example, execution is deferred while the DA client  102  awaits input from the user. Such input may be a response to a strict prompt, as defined above. Because a strict prompt constrains the dialogue between the virtual assistant and the user to a small set of possibilities (e.g., “yes,” “no,” a particular time or date), such input can be handled locally, at the electronic device  104 ,  200 ,  400 ,  600 , without the need to pass a task back to the server  108 . Under some circumstances, it is faster to handle such input locally on the electronic device  104 ,  200 ,  400 ,  600  rather than transmitting a speech waveform to the server  108  and waiting for a response. Instead, for example, upon receiving the user input, the DA client  102  can return to block  996  and determine whether to execute a task based on that user input, or cause  998  execution of that task at the server  108 . The use of strict prompts provides a level of confidence that the electronic device  104 ,  200 ,  400 ,  600  can determine the content of the user input and decide that it does not need to transmit the user input to the server  108  to determine what was said. In the event that the user says something that was not expected (e.g., the user input is formulated in an unexpected way, or is irrelevant to the strict prompt), the DA client can return to block  996 , and then cause  998  execution of the task of recognizing the user input at the server  108 . 
     According to some embodiments, a step in any process  900 ,  940 ,  980  herein includes maintaining the state of each task at both the electronic device  104 ,  200 ,  400 ,  600  and the server  108 . In this way, the DA client  102  and DA server  104  keep track of task execution, and each are configured to expect data from the other when data is arriving from the other. Therefore, in some embodiments, optionally as a result of the determining in block  996  (which can be made by either the DA client  102  or the DA server  106 ) to cause execution of at least one task at the electronic device  104 ,  200 ,  400 ,  600 , the DA server  106  generates  1000  executable code for carrying out the at least one task. Generation of executable code is performed substantially as described above. 
     Optionally, the executable code generated in block  1000  is transmitted  1002  from the server  108  to the electronic device  104 ,  200 ,  400 ,  600 . Optionally, the executable code is then executed  1004  at the electronic device  104 ,  200 ,  400 ,  600 . Optionally, the executable code is performed  1006  in a sandbox at the electronic device  104 ,  200 ,  400 ,  600 . A “sandbox” is a computer security term that refers to a separate computing environment in which code can run in a sequestered area, so that if errors or security issues occur, those issues will not spread to other areas on the electronic device  104 ,  200 ,  400 ,  600 . Programs are enabled in their own sequestered area, where they can be worked on without posing any threat to other programs. A virtual machine is a sandbox, according to some embodiments. 
     Returning to block  996 , in accordance with a determination  996  to execute at least one task at server  108 , the DA server  106  causes  1008  execution of at least one task at the server  108 . Where blocks  990 - 994  have been performed, the determination is based on the server  108  being faster than the electronic device  104 ,  200 ,  400 ,  600  to perform the task, with a difference in speed over a threshold. The execution is performed at processing modules  114 , in some embodiments. In other embodiments, the execution is performed at any suitable hardware element or elements at the server  108 . In some embodiments, in block  1010 , the DA client  102  generates, or causes another component of the electronic device  104 ,  200 ,  400 ,  600  to generate, executable code that executes the at least one task at the server  108 . Generation of executable code is performed substantially as described above. Optionally, the executable code generated in block  1010  is transmitted  1012  from the electronic device  104 ,  200 ,  400 ,  600  to the server  108 . Optionally, the executable code is then executed  1014  at the server  108 . Optionally, the executable code is performed  1016  in a sandbox at the server  108 . 
     Returning to block  996 , where the estimating  986  also includes comparing  990  speeds and comparing  994  the difference in speed to a threshold, as described above, in response to determining that the difference is less than the threshold, the DA client  102  determines  996  that both the server  108  and the electronic device  104 ,  200 ,  400 ,  600  perform the task. In accordance with a determination  996  to execute at least one task at both the server  108  and the electronic device  104 ,  200 ,  400 ,  600  perform the task, the DA client  102  causes  1018  execution of at least one task at both the server  108  and the electronic device  104 ,  200 ,  400 ,  600 . The executable code is executed at both the server  108  and the electronic device  104 ,  200 ,  400 ,  600 , in substantially the same manner as described above with reference to methods  900  and  940 . According to some embodiments, results from execution of at least one task are returned to the electronic device  104 ,  200 ,  400 ,  600  upon completion of each task. Optionally, in block  1020 , the electronic device  104 ,  200 ,  400 ,  600  utilizes the results of the first of the electronic device  104 ,  200 ,  400 ,  600  and the server  108  to execute the task. In block  1022 , the electronic device  104 ,  200 ,  400 ,  600  discards the results of the second of the electronic device  104 ,  200 ,  400 ,  600  and the server  108  to execute the task. As used in this paragraph, the term “execute” includes returning the results to the electronic device  104 ,  200 ,  400 ,  600 . For example, where the server  108  executes the task first, such that the results of the task have been returned to the electronic device  104 ,  200 ,  400 ,  600  before the same task has finished executing on the electronic device  104 ,  200 ,  400 ,  600  itself, the electronic device  104 ,  200 ,  400 ,  600  utilizes the results received from the server  108  and discards the results received from the electronic device  104 ,  200 ,  400 ,  600  when those results are available. 
     In blocks  998 ,  1008 ,  1018 , execution of the code is deferred, according to some embodiments. As one example, execution of the code is associated with an event in the future, such as “set an alarm an hour before my meeting tomorrow.” As another example, execution of the code requires an input, or the acquisition of information, on which execution of the code is based. The ability to defer the execution of code for a non-trivial amount of time, or conditionally upon the acquisition of information, allows for a robust system capable of fulfilling a range of user requests. As set forth above, according to some embodiments, a step in any process  900 ,  940 ,  980  herein includes maintaining the state of each task at both the electronic device  104 ,  200 ,  400 ,  600  and the server  108 . In this way, the DA client  102  and DA server  104  keep track of task execution, and each are configured to expect data from the other when data is arriving from the other. Maintaining state information allows for more effective deferred execution of code, because the electronic device  104 ,  200 ,  400 ,  600  and the server  108  can track data and actions for which a response is still outstanding, and then receive that response back into the process  900 ,  940 ,  980  when it arrives and act upon it. 
       FIG. 10C  shows an exemplary functional block diagram of an electronic device  1300  configured in accordance with the principles of the various described embodiments. In accordance with some embodiments, the functional blocks of electronic device  1300  are configured to perform the techniques described above. The functional blocks of the device  1300  are, optionally, implemented by hardware, software, or a combination of hardware and software to carry out the principles of the various described examples. It is understood by persons of skill in the art that the functional blocks described in  FIG. 10C  are, optionally, combined or separated into sub-blocks to implement the principles of the various described examples. Therefore, the description herein optionally supports any possible combination or separation or further definition of the functional blocks described herein. 
     As shown in  FIG. 10C , an electronic device  1300  optionally includes a display unit  1302  configured to display a graphic user interface; optionally, a touch-sensitive surface unit  1304  configured to receive contacts, a microphone unit  1306  configured to receive audio signals, and a processing unit  1308  optionally coupled to the display unit  1302 , the touch-sensitive surface unit  1304  and/or the microphone unit  1306 . In some embodiments, the processing unit  1308  includes a transmitting unit  1310 , receiving unit  1312 , a determining unit  1314 , an estimating unit  1316 , a causing unit  1318 , optionally a maintaining unit  1320 , and optionally a generating unit  1322 . The electronic device is connected to a second electronic device  1324 . 
     According to some embodiments, a processing unit is configured to receive (e.g., with receiving unit  1312 ) a user request for a service from a virtual assistant at the electronic device  1300 ; determine (e.g., with determining unit  1314 ) at least one task to perform in response to the user request; estimate (e.g., with estimating unit  1316 ) at least one performance characteristic for completion of the at least one task with the first electronic device  1300  and with the second electronic device  1324 , based on at least one heuristic; based on the estimate, determine (e.g., with determining unit  1314 ) whether to execute the at least one task at one of the first electronic device  1300  and the second electronic device  1324 ; in accordance with a determination to execute the at least one task at the first electronic device  1300 , cause (e.g., with causing unit  1318 ) the execution of the at least one task at the first electronic device  1300 ; in accordance with a determination to execute the at least one task at the second electronic device  1324 , cause (e.g., with causing unit  1318 ) the execution of the at least one task at the second electronic device  1324 . 
     In some embodiments, where the first electronic device  1300  includes a battery, the at least one heuristic includes the battery life of the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes availability of high-frequency wireless networking bandwidth complying with the IEEE 802.11x standard at the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes network latency between the first electronic device  1300  and the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes network speed available to the first electronic device  1300  and the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes connection status between the first electronic device  1300  and the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes load at the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes available capacity at the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes status of the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes available memory space of the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes processing speed of the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes operating system of the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes available cache space at the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes type of first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes privacy settings associated with the at least one task. 
     In some embodiments, the at least one heuristic includes data transmission restrictions associated with the at least one task. 
     In some embodiments, the at least one heuristic includes location of the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes location of the first electronic device  1300 . 
     In some embodiments, the at least one heuristic includes the characteristics of the at least one task. 
     In some embodiments, the at least one heuristic includes traffic volume at the second electronic device  1324 . 
     In some embodiments, the at least one heuristic includes user preferences associated with the task. 
     In some embodiments, the at least one heuristic includes characteristics of the task. 
     In some embodiments, the at least one heuristic includes characteristics of a connection from the second electronic device  1324  to a service provider. 
     In some embodiments, the processing unit  1308  further includes a maintaining unit, and the maintaining unit is configured to maintain (e.g., with maintaining unit  1320 ) a state of each task at both the first electronic device  1300  and the second electronic device  1324 . 
     In some embodiments, the processing unit  1308  further includes a comparing unit; wherein the processing unit  1308  is further configured to determine (e.g., with determining unit  1314 ) whether to execute the at least one task at one of the first electronic device  1300  and the second electronic device  1324 ; the processing unit configured to determine (e.g., with determining unit  1314 ) a speed with which each of the first electronic device and the second electronic device  1324  is able to execute the at least one task; and estimate (e.g., with estimating unit  1316 ) the speed with which the first electronic device  1300  is able to execute the at least one task with the speed with which the second electronic device  1324  is able to execute that task. 
     In some embodiments, the processing unit  1308  is further configured to determine (e.g., with determining unit  1314 ) that the difference between the speed with which the first electronic device  1300  is able to execute the at least one task and the speed with which the second electronic device  1324  is able to execute that task is greater than a threshold; and wherein the processing unit is further configured to, in response to a determination that the difference is greater than the threshold, determine (e.g., with determining unit  1314 ) the faster of the first electronic device and the second electronic device to execute the at least one task. 
     In some embodiments, the processing unit  1308  is further configured to determine (e.g., with determining unit  1314 ) that the difference between the speed with which the first electronic device  1300  is able to execute the at least one task and the speed with which the second electronic device  1324  is able to execute that task is less than a threshold; and wherein the processing unit  1308  is further configured to, in response to a determination that the difference is less than the threshold, cause (e.g., with causing unit  1318 ) both the first electronic device  1300  and the second electronic device  1324  to execute the at least one task; cause (e.g., with causing unit  1318 ), at the first electronic device  1300 , the results of the first of the first electronic device  1300  and the second electronic device  1324  to be used to execute the at least one task; and cause (e.g., with causing unit  1318 ), at the first electronic device  1300 , the results of the second of the first electronic device  1300  and the second electronic device  1324  to execute the at least one task to be discarded. 
     In some embodiments, the processing unit  1308  further comprises a generating unit  1322 ; and wherein the processing unit  1308  is further configured to cause (e.g., with causing unit  1318 ) the execution; the processing unit  1308  configured to generate (e.g., with generating unit  1322 ) at one of the first electronic device  1300  and the second electronic device  1324 , executable code for carrying out the least one task; transmit (e.g., with transmitting unit  1310 ) to the other of the first electronic device  1300  and the second electronic device  1324 , the generated executable code; and cause (e.g., with causing unit  1318 ) execution of the executable code at the one of the first electronic device  1300  and the second electronic device  1324  where the executable code is received. 
     The operations described above with reference to  FIGS. 9E-9H  are, optionally, implemented by components depicted in  FIGS. 1A-7C ,  FIG. 8E  and/or  FIG. 10 . It would be clear to a person having ordinary skill in the art how processes can be implemented based on the components depicted in  FIGS. 1A-7C ,  FIG. 8E , and/or  FIG. 10 . 
     The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the techniques and their practical applications. Others skilled in the art are thereby enabled to best utilize the techniques and various embodiments with various modifications as are suited to the particular use contemplated. 
     Although the disclosure and examples have been fully described with reference to the accompanying drawings, it is to be noted that various changes and modifications will become apparent to those skilled in the art. Such changes and modifications are to be understood as being included within the scope of the disclosure and examples as defined by the claims. 
     As described above, one aspect of the present technology is the gathering and use of data available from various sources to improve the delivery to users of content that may be of interest to them. The present disclosure contemplates that in some instances, this gathered data may include personal information data that uniquely identifies or can be used to contact or locate a specific person. Such personal information data can include demographic data, location-based data, telephone numbers, email addresses, home addresses, or any other identifying information. 
     The present disclosure recognizes that the use of such personal information data, in the present technology, can be used to the benefit of users. For example, the personal information data can be used to deliver targeted content that is of greater interest to the user. Accordingly, use of such personal information data enables calculated control of the delivered content. Further, other uses for personal information data that benefit the user are also contemplated by the present disclosure. 
     The present disclosure further contemplates that the entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal information data will comply with well-established privacy policies and/or privacy practices. In particular, such entities should implement and consistently use privacy policies and practices that are generally recognized as meeting or exceeding industry or governmental requirements for maintaining personal information data private and secure. For example, personal information from users should be collected for legitimate and reasonable uses of the entity and not shared or sold outside of those legitimate uses. Further, such collection should occur only after receiving the informed consent of the users. Additionally, such entities would take any needed steps for safeguarding and securing access to such personal information data and ensuring that others with access to the personal information data adhere to their privacy policies and procedures. Further, such entities can subject themselves to evaluation by third parties to certify their adherence to widely accepted privacy policies and practices. 
     Despite the foregoing, the present disclosure also contemplates embodiments in which users selectively block the use of, or access to, personal information data. That is, the present disclosure contemplates that hardware and/or software elements can be provided to prevent or block access to such personal information data. For example, in the case of advertisement delivery services, the present technology can be configured to allow users to select to “opt in” or “opt out” of participation in the collection of personal information data during registration for services. In another example, users can select not to provide location information for targeted content delivery services. In yet another example, users can select to not provide precise location information, but permit the transfer of location zone information. 
     Therefore, although the present disclosure broadly covers use of personal information data to implement one or more various disclosed embodiments, the present disclosure also contemplates that the various embodiments can also be implemented without the need for accessing such personal information data. That is, the various embodiments of the present technology are not rendered inoperable due to the lack of all or a portion of such personal information data. For example, content can be selected and delivered to users by inferring preferences based on non-personal information data or a bare minimum amount of personal information, such as the content being requested by the device associated with a user, other non-personal information available to the content delivery services, or publically available information.

Metadata:
Filing Date: 20160526
Publication Date: 20200602
Grant Date: 20200602
Priority Date: 20150908
Inventors: ZEITLIN, NICOLAS
Assignee: APPLE INC
CPC Classifications: [{"code": "G06F9/5027", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/4843", "inventive": true, "first": true, "tree": "[]"}, {"code": "G10L15/22", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F3/167", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06N3/006", "inventive": false, "first": false, "tree": "[]"}, {"code": "G10L2015/223", "inventive": false, "first": false, "tree": "[]"}, {"code": "G10L15/285", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F16/90332", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L15/30", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/453", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04M3/4936", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F2209/509", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M3/4936", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L15/285", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L15/22", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06N3/006", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F2209/509", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F16/90332", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/453", "inventive": true, "first": true, "tree": "[]"}, {"code": "G10L15/30", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/5027", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/4843", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L2015/223", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F3/167", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F3/167", "inventive": true, "first": true, "tree": "[]"}, {"code": "Y02D10/00", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06N3/006", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F9/5027", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/453", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/5027", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04M3/4936", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F2209/509", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04M3/4936", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/4843", "inventive": true, "first": true, "tree": "[]"}, {"code": "G06F2209/509", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F16/90332", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F9/453", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L15/30", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L2015/223", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06N3/006", "inventive": false, "first": false, "tree": "[]"}, {"code": "G06F3/167", "inventive": true, "first": false, "tree": "[]"}, {"code": "G06F16/90332", "inventive": true, "first": false, "tree": "[]"}, {"code": "G10L15/22", "inventive": false, "first": false, "tree": "[]"}, {"code": "G10L15/22", "inventive": false, "first": false, "tree": "[]"}, {"code": "G10L15/285", "inventive": true, "first": false, "tree": "[]"}]
Family ID: 58190445