Patent Publication Number: US-2021191968-A1

Title: Intelligent automated assistant for media search and playback

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 16/526,751, filed on Jul. 30, 2019, entitled “Intelligent Automated Assistant for Media Search and Playback,” which is a continuation of U.S. application Ser. No. 14/963,089, filed on Dec. 8, 2015, and entitled “Intelligent Automated Assistant for Media Search and Playback,” which claims priority from U.S. Provisional Ser. No. 62/215,575, filed on Sep. 8, 2015, and entitled “Intelligent Automated Assistant for Media Search and Playback.” The content of both applications are hereby incorporated by reference in their entirety for all purposes. 
     This application relates to the following co-pending applications: U.S. Non-Provisional patent application Ser. No. 14/963,094, “Intelligent Automated Assistant in a Media Environment,” filed Dec. 8, 2015 (Attorney Docket No. P25817US1/77870000209101), U.S. Non-Provisional patent application Ser. No. 14/498,503, “Intelligent Automated Assistant for TV User Interactions,” filed Sep. 26, 2014 (Attorney Docket No. P18133US1/77870000161101), and U.S. Non-Provisional patent application Ser. No. 14/498,391, “Real-time Digital Assistant Knowledge Updates,” filed Sep. 26, 2014 (Attorney Docket No. P22498US1/77870000181101), which are hereby incorporated by reference in their entirety for all purposes. 
    
    
     FIELD 
     This relates generally to intelligent automated assistants and, more specifically, to intelligent automated assistants for media search and playback. 
     BACKGROUND 
     Intelligent automated assistants (or digital assistants) can provide an intuitive interface between users and electronic devices. These assistants can 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 input in natural language form to a virtual assistant associated with the electronic device. The virtual assistant can perform natural language processing on the spoken user input to infer the user&#39;s intent and operationalize the user&#39;s intent into tasks. The tasks can then be performed by executing one or more functions of the electronic device, and, in some examples, a relevant output can be returned to the user in natural language form. 
     Integrating digital assistants in a media environment (e.g., televisions, television set-top boxes, cable boxes, gaming devices, streaming media devices, digital video recorders, etc.) can be desirable to assist users with tasks related to media consumption. For example, a digital assistant can be utilized to assist with searching for desirable media content to consume. However, users are often not clear with regard to the specific media item they wish to consume and may spend a considerable amount of time browsing media items to discover new and interesting content. Further, existing search interfaces can be complicated and not user friendly, which can further increase the time a user spends browsing media items before ultimately selecting a desired item to consume. 
     SUMMARY 
     Systems and processes are disclosed for operating a digital assistant in a media environment. In an example process, a primary set of media items can be displayed on a display unit. In response to detecting a user input, audio input can be received. The audio input can contain a media-related request in natural language speech form. A primary user intent corresponding to the media-related request can be determined. The process can determine whether the primary user intent comprises a user intent to narrow a primary media search query corresponding to the primary set of media items. In accordance with a determination that the primary user intent comprises a user intent to narrow the primary media search query, a second primary media search query corresponding to the primary user intent can be generated. The second primary media search query can be based on the media-related request and the primary media search query. The second primary media search query can be performed to obtain a second primary set of media items. Display of the primary set of media items on the display unit can be replaced with display of the second primary set of media items. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating a system and environment for implementing a digital assistant according to various examples. 
         FIG. 2  is a block diagram illustrating a media system according to various examples. 
         FIG. 3  is a block diagram illustrating a user device according to various examples. 
         FIG. 4A  is a block diagram illustrating a digital assistant system or a server portion thereof according to various examples. 
         FIG. 4B  illustrates the functions of the digital assistant shown in  FIG. 4A  according to various examples. 
         FIG. 4C  illustrates a portion of an ontology according to various examples. 
         FIGS. 5A-E  illustrate a process for operating a digital assistant of a media system according to various examples. 
         FIGS. 6A-K  illustrate screen shots displayed by a media device on a display unit at various stages of the process shown in  FIGS. 5A-E  according to various examples. 
         FIG. 7  illustrates a functional block diagram of an electronic device configured to operate a digital assistant of a media system according to various examples. 
     
    
    
     DETAILED DESCRIPTION 
     In the following description of examples, reference is made to the accompanying drawings in which it is shown by way of illustration specific examples that can be practiced. It is to be understood that other examples can be used and structural changes can be made without departing from the scope of the various examples. 
     This disclosure relates to systems and processes for operating a digital assistant in a media environment. In one example process, a media search request in natural language speech form can be received. A primary user intent corresponding to the media search request can be determined. A primary set of media items can be obtained in accordance with the primary user intent. The process can determine whether one or more previous user intents exist, where the one or more previous user intents corresponds to one or more previous media search requests received prior to the media search request. In response to determining that one or more previous user intents exist, one or more secondary user intents can be determined based on the primary user intent and the one or more previous user intents. The one or more secondary user intents can be based on various other factors such as media browsing history, related search attributes, and popular media attributes among a plurality of users. A plurality of secondary sets of media items can be obtained, where each secondary set of media items corresponds to a respective secondary user intent of the one or more secondary user intents. The obtained primary set of media items and the plurality of secondary sets of media items can be displayed, via a user interface, on a display unit for user selection. The primary and secondary user intents can be intelligently determined to increase the probability of predicting the user&#39;s actual intent. By providing a variety of media items based on primary and secondary user intents, a user can be more likely to come across media items that pique the user&#39;s interest. This can be desirable for improving user experience by decreasing the amount of time spent browsing for media items and subsequently increasing the amount of time spent enjoying media content. 
     1. System and Environment 
       FIG. 1  illustrates exemplary system  100  for operating a digital assistant according to various examples. 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, application programming interfaces (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 “What time is it in Paris?” The digital assistant can retrieve the requested information and respond, “It&#39;s 4:00 PM in Paris.” The user can also request the performance of a task, for example, “Find movies starring Reese Witherspoon.” In response, the digital assistant can perform the requested search query and display relevant movie titles for the user to select from. 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 text responses and taking programmed actions, the digital assistant can also provide responses in other visual or audio forms, e.g., as verbal, alerts, music, images, videos, animations, etc. Moreover, as discussed herein, an exemplary digital assistant can control playback of media content (e.g., on a television set-top box) and cause media content or other information to be displayed on a display unit (e.g., a television). 
     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 media device  104  and server-side portion  106  (hereafter “DA server  106 ”) executed on server system  108 . Further, in some examples, the client-side portion can also be executed on user device  122 . 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 device (e.g., media device  104  and user device  122 ). 
     Media device  104  can be any suitable electronic device that is configured to manage and control media content. For example, media device  104  can include television set-top box, such as a cable box device, satellite box device, video player device, video streaming device, digital video recorder, gaming system, DVD player, Blu-ray Disc™ Player, a combination of such devices, or the like. As shown in  FIG. 1 , media device  104  can be part of media system  128 . In addition to media device  104 , media system  128  can include remote control  124  and display unit  126 . Media device  104  can display media content on display unit  126 . Display unit  126  can be any type of display, such as a television display, monitor, projector, or the like. In some examples, media device  104  can connect to an audio system (e.g., audio receiver), and speakers (not shown) that can be integrated with or separate from display unit  126 . In other examples, display unit  126  and media device  104  can be incorporated together in a single device, such as a smart television with advanced processing and network connectivity capabilities. In such examples, the functions of media device  104  can be executed as an application on the combined device. 
     In some examples, media device  104  can function as a media control center for multiple types and sources of media content. For example, media device  104  can facilitate user access to live television (e.g., over-the-air, satellite, or cable TV). As such, media device  104  can include cable tuners, satellite tuners, or the like. In some examples, media device  104  can also record TV programs for later time-shifted viewing. In other examples, media device  104  can provide access to one or more streaming media services, such as cable-delivered on-demand TV shows, videos, and music as well as internet-delivered TV shows, videos, and music (e.g., from various free, paid, and subscription-based streaming services). In still other examples, media device  104  can facilitate playback or display of media content from any other source, such as displaying photos from a mobile user device, playing videos from a coupled storage device, playing music from a coupled music player, or the like. Media device  104  can also include various other combinations of the media control features discussed herein, as desired. A detailed description of media device  104  is provided below with reference to  FIG. 2 . 
     User device  122  can be any personal electronic device, such as a mobile phone (e.g., smartphone), tablet computer, portable media player, desktop computer, laptop computer, PDA, wearable electronic device (e.g., digital glasses, wristband, wristwatch, brooch, armband, etc.), or the like. A detailed description of user device  122  is provided below with reference to  FIG. 3 . 
     In some examples, a user can interact with media device  104  through user device  122 , remote control  124 , or interface elements integrated with media device  104  (e.g., buttons, a microphone, a camera, a joystick, etc.). For example, speech input including media-related queries or commands for the digital assistant can be received at user device  122  and/or remote control  124 , and the speech input can be used to cause media-related tasks to be executed on media device  104 . Likewise, tactile commands for controlling media on media device  104  can be received at user device  122  and/or remote control  124  (as well as from other devices not shown). The various functions of media device  104  can thus be controlled in a variety of ways, giving users multiple options for controlling media content from multiple devices. 
     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. 
     DA server  106  can include client-facing input/output (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 IO 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  can perform task execution based on inferred user intent. In some examples, DA server  106  can communicate with external services  120 , such as telephony services, calendar services, information services, messaging services, navigation services, television programming services, streaming media services, media search services, and the like, through network(s)  110  for task completion or information acquisition. I/O interface to external services  118  can facilitate such communications. 
     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 . 
     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 or a media 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 executed on user device  122  or media device  104  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. 
     2. Media System 
       FIG. 2  illustrates a block diagram of media system  128  according to various examples. Media system  128  can include media device  104  that is communicatively coupled to display unit  126 , remote control  124 , and speakers  268 . Media device  104  can receive user input via remote control  124 . Media content from media device  104  can be displayed on display unit  126 . 
     In the present example, as shown in  FIG. 2 , media device  104  can include memory interface  202 , one or more processors  204 , and a peripherals interface  206 . The various components in media device  104  can be coupled together by one or more communication buses or signal lines. Media device  104  can further include various subsystems and peripheral devices that are coupled to the peripherals interface  206 . The subsystems and peripheral devices can gather information and/or facilitate various functionalities of media device  104 . 
     For example, media device  104  can include a communication subsystem  224 . Communication functions can be facilitated through one or more wired and/or wireless communication subsystems  224 , which can include various communication ports, radio frequency receivers and transmitters, and/or optical (e.g., infrared) receivers and transmitters. 
     In some examples, media device  104  can further include an I/O subsystem  240  coupled to peripherals interface  206 . I/O subsystem  240  can include an audio/video output controller  270 . Audio/video output controller  270  can be coupled to display unit  126  and speakers  268  or can otherwise provide audio and video output (e.g., via audio/video ports, wireless transmission, etc.). I/O subsystem  240  can further include remote controller  242 . Remote controller  242  can be communicatively coupled to remote control  124  (e.g., via a wired connection, BLUETOOTH, Wi-Fi, etc.). 
     Remote control  124  can include microphone  272  for capturing audio data (e.g., speech input from a user), button(s)  274  for capturing tactile input, and transceiver  276  for facilitating communication with media device  104  via remote controller  242 . Further, remote control  124  can include a touch-sensitive surface  278 , sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact. Touch-sensitive surface  278  and remote controller  242  can detect contact (and any movement or breaking of the contact) on touch-sensitive surface  278  and convert the detected contact (e.g., gestures, contact motions, etc.) into interaction with user-interface objects (e.g., one or more soft keys, icons, web pages, or images) that are displayed on display unit  126 . In some examples, remote control  124  can also include other input mechanisms, such as a keyboard, joystick, or the like. In some examples, remote control  124  can further include output mechanisms, such as lights, a display, a speaker, or the like. Input received at remote control  124  (e.g., user speech, button presses, contact motions, etc.) can be communicated to media device  104  via remote control  124 . I/O subsystem  240  can also include other input controller(s)  244 . Other input controller(s)  244  can be coupled to other input/control devices  248 , such as one or more buttons, rocker switches, a thumb-wheel, an infrared port, a USB port, and/or a pointer device, such as a stylus. 
     In some examples, media device  104  can further include a memory interface  202  coupled to memory  250 . Memory  250  can include any electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device; a portable computer diskette (magnetic); a random access memory (RAM) (magnetic); a read-only memory (ROM) (magnetic); an erasable programmable read-only memory (EPROM) (magnetic); a portable optical disc such as CD, CD-R, CD-RW, DVD, DVD-R, or DVD-RW; or flash memory such as compact flash cards, secured digital cards, USB memory devices, memory sticks, and the like. In some examples, a non-transitory computer-readable storage medium of memory  250  can be used to store instructions (e.g., for performing portions or all of the various processes described herein) 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 can execute the instructions. In other examples, the instructions (e.g., for performing portions or all of the various processes described herein) can be stored on a non-transitory computer-readable storage medium of server system  108 , or can be divided between the non-transitory computer-readable storage medium of memory  250  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 non-transitory medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device. 
     In some examples, memory  250  can store an operating system  252 , a communication module  254 , a graphical user interface (GUI) module  256 , an on-device media module  258 , an off-device media module  260 , and an applications module  262 . Operating system  252  can include instructions for handling basic system services and for performing hardware-dependent tasks. Communication module  254  can facilitate communicating with one or more additional devices, one or more computers, and/or one or more servers. Graphical user interface module  256  can facilitate graphical user interface processing. On-device media module  258  can facilitate storage and playback of media content stored locally on media device  104 . Off-device media module  260  can facilitate streaming playback or download of media content obtained from an external source (e.g., on a remote server, on user device  122 , etc.). Further, off-device media module  260  can facilitate receiving broadcast and cable content (e.g., channel tuning). Applications module  262  can facilitate various functionalities of media-related applications, such as web browsing, media processing, gaming, and/or other processes and functions. 
     As described herein, memory  250  can also store client-side digital assistant instructions (e.g., in a digital assistant client module  264 ) and various user data  266  (e.g., user-specific vocabulary data, preference data, and/or other data such as the user&#39;s media search history, media watch list, recently watched list, favorite media items, etc.) to, for example, provide the client-side functionalities of the digital assistant. User data  266  can also be used in performing speech recognition in support of the digital assistant or for any other application. 
     In various examples, digital assistant client module  264  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., I/O subsystem  240  or the like) of media device  104 . Digital assistant client module  264  can also be capable of providing output in audio (e.g., speech output), visual, and/or tactile forms. 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  264  can communicate with the digital assistant server (e.g., DA server  106 ) using communication subsystem  224 . 
     In some examples, digital assistant client module  264  can utilize the various subsystems and peripheral devices to gather additional information related to media device  104  and from the surrounding environment of media device  104  to establish a context associated with a user, the current user interaction, and/or the current user input. Such context can also include information from other devices, such as from user device  122 . In some examples, digital assistant client module  264  can provide the contextual information or a subset thereof with the user input to the digital assistant server to help infer the user&#39;s intent. The digital assistant can also use the contextual information to determine how to prepare and deliver outputs to the user. The contextual information can further be used by media device  104  or server system  108  to support accurate speech recognition. 
     In some examples, the contextual information that accompanies the user input can include sensor information, such as lighting, ambient noise, ambient temperature, distance to another object, and the like. The contextual information can further include information associated with the physical state of media device  104  (e.g., device location, device temperature, power level, etc.) or the software state of media device  104  (e.g., running processes, installed applications, past and present network activities, background services, error logs, resources usage, etc.). The contextual information can further include information received from the user (e.g., speech input), information requested by the user, and information presented to the user (e.g., information currently or previously displayed by the media device). The contextual information can further include information associated with the state of connected devices or other devices associated with the user (e.g., content displayed on user device  122 , playable content on user device  122 , etc.). Any of these types of contextual information can be provided to DA server  106  (or used on media device  104  itself) as contextual information associated with a user input. 
     In some examples, digital assistant client module  264  can selectively provide information (e.g., user data  266 ) stored on media device  104  in response to requests from DA server  106 . Additionally or alternatively, the information can be used on media device  104  itself in executing speech recognition and/or digital assistant functions. Digital assistant client module  264  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  264  can pass the additional input to DA server  106  to help DA server  106  in intent inference and/or fulfillment of the user&#39;s intent expressed in the user request. 
     In various examples, memory  250  can include additional instructions or fewer instructions. Furthermore, various functions of media device  104  can be implemented in hardware and/or in firmware, including in one or more signal processing and/or application specific integrated circuits. 
     3. User Device 
       FIG. 3  illustrates a block diagram of exemplary user device  122  according to various examples. As shown, user device  122  can include a memory interface  302 , one or more processors  304 , and a peripherals interface  306 . The various components in user device  122  can be coupled together by one or more communication buses or signal lines. User device  122  can further include various sensors, subsystems, and peripheral devices that are coupled to the peripherals interface  306 . The sensors, subsystems, and peripheral devices can gather information and/or facilitate various functionalities of user device  122 . 
     For example, user device  122  can include a motion sensor  310 , a light sensor  312 , and a proximity sensor  314  coupled to peripherals interface  306  to facilitate orientation, light, and proximity-sensing functions. One or more other sensors  316 , such as a positioning system (e.g., a GPS receiver), a temperature sensor, a biometric sensor, a gyroscope, a compass, an accelerometer, and the like, can also be connected to peripherals interface  306 , to facilitate related functionalities. 
     In some examples, a camera subsystem  320  and an optical sensor  322  can be utilized to facilitate camera functions, such as taking photographs and recording video clips. Communication functions can be facilitated through one or more wired and/or wireless communication subsystems  324 , which can include various communication ports, radio frequency receivers and transmitters, and/or optical (e.g., infrared) receivers and transmitters. An audio subsystem  326  can be coupled to speakers  328  and microphone  330  to facilitate voice-enabled functions, such as voice recognition, voice replication, digital recording, and telephony functions. 
     In some examples, user device  122  can further include an I/O subsystem  340  coupled to peripherals interface  306 . I/O subsystem  340  can include a touchscreen controller  342  and/or other input controller(s)  344 . Touchscreen controller  342  can be coupled to a touchscreen  346 . Touchscreen  346  and the touchscreen controller  342  can, for example, detect contact and movement or break thereof using any of a plurality of touch-sensitivity technologies, such as capacitive, resistive, infrared, and surface acoustic wave technologies; proximity sensor arrays; and the like. Other input controller(s)  344  can be coupled to other input/control devices  348 , such as one or more buttons, rocker switches, a thumb-wheel, an infrared port, a USB port, and/or a pointer device, such as a stylus. 
     In some examples, user device  122  can further include a memory interface  302  coupled to memory  350 . Memory  350  can include any electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device; a portable computer diskette (magnetic); a random access memory (RAM) (magnetic); a read-only memory (ROM) (magnetic); an erasable programmable read-only memory (EPROM) (magnetic); a portable optical disc such as CD, CD-R, CD-RW, DVD, DVD-R, or DVD-RW; or flash memory such as compact flash cards, secured digital cards, USB memory devices, memory sticks, and the like. In some examples, a non-transitory computer-readable storage medium of memory  350  can be used to store instructions (e.g., for performing portions or all of the various processes described herein) 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 can execute the instructions. In other examples, the instructions (e.g., for performing portions or all of the various processes described herein) can be stored on a non-transitory computer-readable storage medium of server system  108 , or can be divided between the non-transitory computer-readable storage medium of memory  350  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 non-transitory medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device. 
     In some examples, memory  350  can store an operating system  352 , a communication module  354 , a graphical user interface (GUI) module  356 , a sensor processing module  358 , a phone module  360 , and an applications module  362 . Operating system  352  can include instructions for handling basic system services and for performing hardware-dependent tasks. Communication module  354  can facilitate communicating with one or more additional devices, one or more computers, and/or one or more servers. Graphical user interface module  356  can facilitate graphical user interface processing. Sensor processing module  358  can facilitate sensor-related processing and functions. Phone module  360  can facilitate phone-related processes and functions. Applications module  362  can facilitate various functionalities of user applications, such as electronic messaging, web browsing, media processing, navigation, imaging, and/or other processes and functions. 
     As described herein, memory  350  can also store client-side digital assistant instructions (e.g., in a digital assistant client module  364 ) and various user data  366  (e.g., user-specific vocabulary data, preference data, and/or other data such as the user&#39;s electronic address book, to-do lists, shopping lists, television program favorites, etc.) to, for example, provide the client-side functionalities of the digital assistant. User data  366  can also be used in performing speech recognition in support of the digital assistant or for any other application. Digital assistant client module  364  and user data  366  can be similar or identical to digital assistant client module  264  and user data  266 , respectively, as described above with reference to  FIG. 2 . 
     In various examples, memory  350  can include additional instructions or fewer instructions. Furthermore, various functions of user device  122  can be implemented in hardware and/or in firmware, including in one or more signal processing and/or application-specific integrated circuits. 
     In some examples, user device  122  can be configured to control aspects of media device  104 . For example, user device  122  can function as a remote control (e.g., remote control  124 . User input received via user device  122  can be transmitted (e.g., using communication subsystem) to media device  104  to cause corresponding actions to be performed by media device  104 . In addition, user device  122  can be configured to receive instructions from media device  104 . For example, media device  104  can hand off tasks to user device  122  to perform and cause objects (e.g., selectable affordances) to be displayed on user device  122 . 
     It should be understood that system  100  and media system  128  are not limited to the components and configuration shown in  FIG. 1  and  FIG. 2 , and user device  122 , media device  104 , and remote control  124  are likewise not limited to the components and configuration shown in  FIG. 2  and  FIG. 3 . System  100 , media system  128 , user device  122 , media device  104 , and remote control  124  can all include fewer or other components in multiple configurations according to various examples. 
     4. Digital Assistant System 
       FIG. 4A  illustrates a block diagram of digital assistant system  400  in accordance with various examples. In some examples, digital assistant system  400  can be implemented on a standalone computer system. In some examples, digital assistant system  400  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  or  122 ) 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  400  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  400  is only one example of a digital assistant system, and that digital assistant system  400  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. 4A  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  400  can include memory  402 , one or more processors  404 , I/O interface  406 , and network communications interface  408 . These components can communicate with one another over one or more communication buses or signal lines  410 . 
     In some examples, memory  402  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  406  can couple I/O devices  416  of digital assistant system  400 , such as displays, keyboards, touch screens, and microphones, to user interface module  422 . I/O interface  406 , in conjunction with user interface module  422 , can receive user inputs (e.g., voice input, keyboard inputs, touch inputs, etc.) and process them accordingly. In some examples, e.g., when the digital assistant is implemented on a standalone user device, digital assistant system  400  can include any of the components and I/O communication interfaces described with respect to devices  104  or  122  in  FIG. 2 or 3 , respectively. In some examples, digital assistant system  400  can represent the server portion of a digital assistant implementation, and can interact with the user through a client-side portion residing on a client device (e.g., devices  104  or  122 ). 
     In some examples, the network communications interface  408  can include wired communication port(s)  412  and/or wireless transmission and reception circuitry  414 . 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  414  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  408  can enable communication between digital assistant system  400  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  402 , or the computer-readable storage media of memory  402 , can store programs, modules, instructions, and data structures including all or a subset of: operating system  418 , communication module  420 , user interface module  422 , one or more applications  424 , and digital assistant module  426 . In particular, memory  402 , or the computer-readable storage media of memory  402 , can store instructions for performing process  800 , described below. One or more processors  404  can execute these programs, modules, and instructions, and can read/write from/to the data structures. 
     Operating system  418  (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  420  can facilitate communications between digital assistant system  400  with other devices over network communications interface  408 . For example, communications module  420  can communicate with the communication subsystems (e.g.,  224 ,  324 ) of electronic devices (e.g.,  104 ,  122 ). Communications module  420  can also include various components for handling data received by wireless circuitry  414  and/or wired communications port  412 . 
     User interface module  422  can receive commands and/or inputs from a user via I/O interface  406  (e.g., from a keyboard, touchscreen, pointing device, controller, and/or microphone), and generate user interface objects on a display. User interface module  422  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  406  (e.g., through displays, audio channels, speakers, touch-pads, etc.). 
     Applications  424  can include programs and/or modules that are configured to be executed by one or more processors  404 . For example, if digital assistant system  400  is implemented on a standalone user device, applications  424  can include user applications, such as games, a calendar application, a navigation application, or an email application. If digital assistant system  400  is implemented on a server, applications  424  can include resource management applications, diagnostic applications, or scheduling applications, for example. 
     Memory  402  can also store digital assistant module  426  (or the server portion of a digital assistant). In some examples, digital assistant module  426  can include the following sub-modules, or a subset or superset thereof: I/O processing module  428 , speech-to-text (STT) processing module  430 , natural language processing module  432 , dialogue flow processing module  434 , task flow processing module  436 , service processing module  438 , and speech synthesis module  440 . Each of these modules can have access to one or more of the following systems or data and models of the digital assistant module  426 , or a subset or superset thereof: ontology  460 , vocabulary index  444 , user data  448 , task flow models  454 , service models  456 , and automatic speech recognition (ASR) systems  431 . 
     In some examples, using the processing modules, data, and models implemented in digital assistant module  426 , 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. 4B , I/O processing module  428  can interact with the user through I/O devices  416  in  FIG. 4A  or with an electronic device (e.g., devices  104  or  122 ) through network communications interface  408  in  FIG. 4A  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  428  can optionally obtain contextual information associated with the user input from the electronic 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 electronic 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  428  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  428  and the user request can include speech input, I/O processing module  428  can forward the speech input to STT processing module  430  (or speech recognizer) for speech-to-text conversions. 
     STT processing module  430  can include one or more ASR systems (e.g., ASR systems  431 ). The one or more ASR systems can process the speech input that is received through I/O processing module  428  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 electronic device (e.g., device  104  or  122 ) to produce the recognition result. Once STT processing module  430  produces recognition results containing a text string (e.g., words, sequence of words, or sequence of tokens), the recognition result can be passed to natural language processing module  432  for intent deduction. 
     In some examples, one or more language models of the one or more ASR systems can be configured to be biased toward media-related results. In one example, the one or more language models can be trained using a corpus of media-related text. In another example, the ASR system can be configured to favor media-related recognition results. In some examples, the one or more ASR systems can include static and dynamic language models. Static language models can be trained using general corpuses of text, while dynamic language models can be trained using user-specific text. For example, text corresponding to previous speech input received from users can be used to generate dynamic language models. In some examples, the one or more ASR systems can be configured to generate recognition results that are based on static language models and/or dynamic language models. Further, in some examples, the one or more ASR systems can be configured to favor recognition results that correspond to previous speech input that is more recently received. 
     Additional 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  430  can include and/or access a vocabulary of recognizable words via phonetic alphabet conversion module  431 . 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  430  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  430  can be used to determine the phonemes corresponding to the speech input (e.g., using an acoustic model), and can then attempt to determine words that match the phonemes (e.g., using a language model). For example, if STT processing module  430  can first identify the sequence of phonemes / / corresponding to a portion of the speech input, it can then determine, based on vocabulary index  444 , that this sequence corresponds to the word “tomato.” 
     In some examples, STT processing module  430  can use approximate matching techniques to determine words in an utterance. Thus, for example, the STT processing module  430  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. 
     Natural language processing module  432  (“natural language processor”) of the digital assistant can take the sequence of words or tokens (“token sequence”) generated by STT processing module  430 , 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  454 . 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  454 , 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  430 , natural language processing module  432  can also receive contextual information associated with the user request, e.g., from/O processing module  428 . The natural language processing module  432  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  430 . 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  460 . Ontology  460  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  460  can define how a parameter represented by the property node pertains to the task represented by the actionable intent node. 
     In some examples, ontology  460  can be made up of actionable intent nodes and property nodes. Within ontology  460 , 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. 4C , ontology  460  can include a “media” node (i.e., an actionable intent node). Property nodes “actor(s),” “media genre,” and “media title,” can each be directly linked to the actionable intent node (i.e., the “media search” node). In addition, property nodes “name,” “age,” “Ulmer scale ranking,” and “nationality” can be sub-nodes of the property node “actor.” 
     In another example, as shown in  FIG. 4C , ontology  460  can also include a “weather” node (i.e., another actionable intent node). Property nodes “date/time” and “location” can each be linked to the “weather search” node. It should be recognized that in some examples, one or more property nodes can be relevant to two or more actionable intents. In these examples, the one or more property nodes can be linked to the respective nodes corresponding to the two or more actionable intents in ontology  460 . 
     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 can refer to the group of nodes (and the relationships there between) associated with the particular actionable intent. For example, ontology  460  shown in  FIG. 4C  can include an example of media domain  462  and an example of weather domain  464  within ontology  460 . Media domain  462  can include the actionable intent node “media search” and property nodes “actor(s),” “media genre,” and “media title.” Weather domain  464  can include the actionable intent node “weather search,” and property nodes “location” and “date/time.” In some examples, ontology  460  can be made up of many domains. Each domain can share one or more property nodes with one or more other domains. 
     While  FIG. 4C  illustrates two example domains within ontology  460 , other domains can include, for example, “athletes,” “stocks,” “directions,” “media settings,” “sports team,” and “time,” “tell joke,” and so on. An “athletes” domain can be associated with a “search athlete information” actionable intent node, and may further include property nodes such as “athlete name,” “athlete team,” and “athlete statistics.” 
     In some examples, ontology  460  can include all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon. In some examples, ontology  460  can be modified, such as by adding or removing entire domains or nodes, or by modifying relationships between the nodes within the ontology  460 . 
     In some examples, each node in ontology  460  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  444  in association with the property or actionable intent represented by the node. For example, returning to  FIG. 4C , the vocabulary associated with the node for the property of “actor” can include words such as “A-list,” “Reese Witherspoon,” “Arnold Schwarzenegger,” “Brad Pitt,” and so on. For another example, the vocabulary associated with the node for the actionable intent of “weather search” can include words and phrases such as “weather,” “what&#39;s it like in,” “forecast,” and so on. The vocabulary index  444  can optionally include words and phrases in different languages. 
     Natural language processing module  432  can receive the token sequence (e.g., a text string) from STT processing module  430 , 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  460  (via vocabulary index  444 ), 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  432  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  448  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. In some examples, natural language processing module  432  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 “How&#39;s the weather this week,” natural language processing module  432  can access user data  448  to determine where the user is located, rather than requiring the user to provide such information explicitly in his/her request. 
     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  432  identifies an actionable intent (or domain) based on the user request, natural language processing module  432  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 “Find me other seasons of this TV series.” In this case, natural language processing module  432  can correctly identify the actionable intent to be “media search” based on the user input. According to the ontology, a structured query for a “media” domain may include parameters such as {media actor}, {media genre}, {media title}, and the like. In some examples, based on the speech input and the text derived from the speech input using STT processing module  430 , natural language processing module  432  can generate a partial structured query for the restaurant reservation domain, where the partial structured query includes the parameters {media genre=“television series” }. 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 {media title} may not be specified in the structured query based on the information currently available. In some examples, natural language processing module  432  can populate some parameters of the structured query with received contextual information. For example, the TV series “Mad Men” can be currently playing on the media device. Based on this contextual information, natural language processing module  432  can populate the {media title} parameter in the structured query with “Mad Men.” 
     In some examples, natural language processing module  432  can pass the generated structured query (including any completed parameters) to task flow processing module  436  (“task flow processor”). Task flow processing module  436  can be configured to receive the structured query from natural language processing module  432 , 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  454 . In some examples, task flow models  454  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  436  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  436  can invoke dialogue flow processing module  434  to engage in a dialogue with the user. In some examples, dialogue flow processing module  434  can determine how (and/or when) to ask the user for the additional information and can receive and process the user responses. The questions can be provided to and answers can be received from the users through I/O processing module  428 . In some examples, dialogue flow processing module  434  can present dialogue output to the user via audio and/or visual output, and can receive input from the user via spoken or physical (e.g., clicking) responses. For example, the user may ask “What&#39;s the weather like in Paris?” When task flow processing module  436  invokes dialogue flow processing module  434  to determine the “location” information for the structured query associated with the domain “weather search,” dialogue flow processing module  434  can generate questions such as “Which Paris?” to pass to the user. Additionally, dialogue flow processing module  434  can cause affordances associated with “Paris, Texas” and “Paris, France” to be presented for user selection. Once a response is received from the user, dialogue flow processing module  434  can then populate the structured query with the missing information, or pass the information to task flow processing module  436  to complete the missing information from the structured query. 
     Once task flow processing module  436  has completed the structured query for an actionable intent, task flow processing module  436  can proceed to perform the ultimate task associated with the actionable intent. Accordingly, task flow processing module  436  can execute the steps and instructions in task flow model  454  according to the specific parameters contained in the structured query. For example, the task flow model for the actionable intent of “media search” can include steps and instructions for performing a media search query to obtain relevant media items. For example, using a structured query such as: {media search, media genre=TV series, media title=Mad Men}, task flow processing module  436  can perform the steps of: (1) performing a media search query using a media database to obtain relevant media items, (2) ranking the obtained media items according to relevancy and/or popularity, and (3) displaying the media items sorted according to relevancy and/or popularity. 
     In some examples, task flow processing module  436  can employ the assistance of service processing module  438  (“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  438  can act on behalf of task flow processing module  436  to perform a media search, retrieve weather information, invoke or interact with applications installed on other user devices, and invoke or interact with third-party services (e.g., a social networking website, media review websites, media subscription services, etc.). In some examples, the protocols and API required by each service can be specified by a respective service model among service models  456 . Service processing module  438  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, a third-party media search service can submit a service model specifying the necessary parameters for performing a media search and the APIs for communicating the values of the necessary parameters to the media search service. When requested by task flow processing module  436 , service processing module  438  can establish a network connection with the media search service and send the necessary parameters of the media search (e.g., media actor, media genre, media title) to the online reservation interface in a format according to the API of the media search service. 
     In some examples, natural language processing module  432 , dialogue flow processing module  434 , and task flow processing module  436  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  440  (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  440  can be configured to synthesize speech outputs for presentation to the user. Speech synthesis module  440  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  440  can convert the text string to an audible speech output. Speech synthesis module  440  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  440  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 module  440  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  440 , 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. 
     4. Process for Operating a Digital Assistant in a Media Environment 
       FIGS. 5A-E  illustrate process  500  for operating a digital assistant of a media system according to various examples. Process  500  can be performed using one or more electronic devices implementing a digital assistant. For example, process  500  can be performed using one or more of system  100 , media system  128 , media device  104 , user device  122 , or digital assistant system  400 , described above.  FIGS. 6A-K  depict screen shots displayed by a media device on a display unit at various stages of process  500 , according to various examples. Process  500  is described below with simultaneous reference to  FIGS. 5A-E  and  6 A-K. It should be appreciated that some operations in process  500  can be combined, the order of some operations can be changed, and some operations can be omitted. 
     At block  502  of process  500  and with reference to  FIG. 6A , primary set of media items  604  can be displayed on a display unit. Each media item can correspond to specific media content (e.g., a movie, video, television show/series, video game, etc.). Primary set of media items  604  can be displayed in response to a previously received media search request. In some examples, the previously received media search request can be a spoken interaction with the digital assistant. In other examples, the previously received media search request can be text interaction with the digital assistant received via a keyboard interface of the media device. 
     Primary set of media items  604  can be obtained by performing a primary media search query in accordance with the previously received media search request. In some examples, the primary media search query can be a structured search based on one or more parameter values defined in the previously received media search request. In these examples, each media item of primary set of media items  604  can include one or more parameter values that match the one or more parameter values defined in the previously received media search request. In other examples, the primary media search query can be a string search based on a text input string of the previously received media search request. In these examples, each media item of primary set of media items  604  can be associated with text that matches the text input string of the previously received media search request. 
     Media items  604  can share common attributes or parameter values corresponding to the previously received media search request. In the present example shown in  FIG. 6A , the previously received media search request can be a request for action movies from the last 10 year. Primary set of media items  604  can be obtained to satisfy the previously received media search request. In this example, primary set of media items  604  can include action movies such as “THE AMAZING SPIDERMAN 2,” “FURIOUS 7,” and “IRON MAN 3,” which were released in the last 10 years. Text  607  describing the attributes or parameter values corresponding to the previously received media search request can be displayed in association with primary set of media items  604 . 
     As shown in  FIG. 6A , primary set of media items  604  can be displayed via user interface  602 . User interface  602  can be configured to enable the user to navigate through the media items in user interface  602  and select a particular media item for consumption. In some examples, one or more secondary sets of media items  606  can be displayed with primary set of media items  604  in user interface  602 . It should be recognized that secondary sets of media items may not always be displayed. In some examples, user interface  602  can occupy at least a majority of a display area of the display unit. In other examples, the display unit can display media content (not shown) playing on the media device while displaying user interface  602 . In these examples, the display area occupied by user interface  602  on the display unit can be smaller than the display area occupied by the media content on the display unit. Further, in these examples, user interface  602  may not include secondary sets of media items  606 . In particular, the only media items displayed via user interface  602  can be primary set of media items  604 . 
     Each displayed media item of primary set of media items  604  and secondary set of media items  606  can be associated with parameter values of parameters such as media type, media title, actors, media characters, director, media release date, media duration, media quality rating, media popularity rating, and the like. In some examples, one or more parameter values of each media item may be displayed, via user interface  602 , as text on or adjacent to the respective media item. 
     In the present example, the one or more secondary sets of media items  606  can be based on the primary set of media items  604 . In particular, the one or more secondary sets of media items  606  can share a common attribute or parameter value with the primary set of media items  604 . As shown in  FIG. 6A , secondary set of media items  608  can be action movies and secondary set of media items  610  can be foreign action movies. Thus, in this example, the primary and secondary sets of media items  604  and  606  can all relate to the media genre of action movies. It should be recognized that in other examples, secondary sets of media items  606  can be based on parameter values derived from other information, such as previous media search requests or popular trending media items and categories. 
     At block  504  of process  500 , a user input can be detected. The user input can be detected while primary set of media items  604  are displayed at block  502 . In some examples, the user input can be detected on a remote control (e.g., remote control  124 ) of the media device. In particular, the user input can be a user interaction with the remote control, such as the pressing of a button (e.g., button  274 ) or the contacting of a touch-sensitive surface (e.g., touch-sensitive surface  278 ) of the remote control. In some examples, the user input can be detected via a second electronic device (e.g., device  122 ) that is configured to interact with the media device. The user input can be associated with invoking the digital assistant of the media device. In response to detecting the user input, one or more of blocks  506 - 510  can be performed. 
     At block  506  of process  500 , an audio input can be received. The audio input can contain a media-related request. For example, in response to detecting the user input at block  504 , audio input can be sampled via a microphone (e.g., microphone  272 ) of the media device. The sampled audio input can include a media-related request in the form of a user utterance. In some examples, the audio input containing the media-related request can be received while at least a portion of primary set of media items  604  is displayed. The media-related request can be in natural language form. In some examples, the media-related request can be underspecified, where not all of the information needed to satisfy the request is explicitly defined. For example, the media-related request can be: “Jack Ryan.” In this example, the request does not explicitly specify whether it is a new media search request for movies with the character Jack Ryan or a request to filter the currently displayed media items based on the character Jack Ryan. 
     In some examples, the media-related request can include one or more ambiguous terms. For example, the media-related request can be: “Which are the good ones?” In this example, the media-related request includes the ambiguous term “ones” that is intended to refer to the media items (e.g., primary and/or secondary sets of media items  604 ,  606 ) being displayed. Further, in this example, the media-related request defines a parameter value (e.g., user rating or critic rating) of the media items using an ambiguous term (e.g., “good”). 
     The media-related request can define one or more parameter values associated with media items. Examples of parameter values that can be defined in the media-related request include media type, media title, actors, media characters, media director, media release date, media duration, media quality rating, media popularity rating, and the like. 
     In some examples, the media-related request can be a media search request. In some examples, the media-related request can be a request to correct the primary media search query. In other examples, the media-related request can be a request to navigate through media items displayed on user interface  602 . In yet other examples, the media-related request can be a request to adjust the state or setting of an application of the media device. 
     Although in the present example, the media-related request is received in an audio input, it should be appreciated that in other examples, the media-related request can be received as text input. In particular, in place of audio input, text input containing the media-related request can be received at block  506  via a key board interface. It should be recognized that block  508  need not be performed in examples where the media-related request is received as text input. Rather, the primary user intent can be determined directly from the text input at block  510 . 
     At block  508  of process  500 , a text representation of the media-related request can be determined. For example, the text representation can be determined by performing speech-to-text (STT) processing on the audio input received at block  506 . In particular, the audio input can be processed using a STT processing module (e.g., STT processing module  430 ) to convert the media-related request in the audio input into the text representation. The text representation can be a token string representing a corresponding text string. In some examples, the text representation can be displayed on the display unit. In particular, the text representation can be displayed in real-time while the audio input is being received at block  506 . 
     One or more language models can be used during STT processing to determine the text representation. In some examples, the STT processing can be biased toward media-related text results. Specifically, the one or more language models used to determine the text representation can be biased towards media-related text results. For example, the one or more language models can be trained using a corpus of media-related text. Additionally or alternatively, the biasing can be implemented by more heavily weighting candidate text results that are related to media. In this way, candidate text results that are related to media can be ranked higher with the biasing than without the biasing. The biasing can be desirable for increasing the accuracy of STT processing for media-related words or phrases in the media-related request (e.g., movie names, movie actors, etc.). For example, certain media-related words or phrases, such as “JURASSIC PARK,” “Arnold Schwarzenegger,” and “SHREK,” can be infrequently found in typical corpuses of text and thus may not be recognized successfully during STT processing without biasing toward media-related text results. 
     As described above, text associated with the media items (e.g., primary set of media items  604  and secondary sets of media items  606 ) displayed at block  502  may be displayed via user interface  602 . The text may describe one or more attributes or parameter values of each media item in user interface  602 . For example, primary set of media items  604  may include a media item corresponding to the movie “IRON MAN 3.” In this example, the displayed text could include the title “IRON MAN 3,” the actors “Robert Downey Jr” and “Gwyneth Paltrow,” and the director “Shane Black.” In some examples, a custom language model can be generated using the displayed text associated with the displayed media items. STT processing can then be performed using the custom language model to determine the text representation. In particular, candidate text results from the custom language model can be afforded greater weight relative to candidate text results from other language models when determining the text representation. It should be recognized that in some examples, not all attributes or parameter values associated with primary set of media items  604  and secondary sets of media items  606  may be displayed as text on the display unit. In these examples, text of the attributes or parameter values of primary set of media items  604  and secondary sets of media items  606  not displayed on the display unit can also be used to generate the custom language model. 
     In some examples, a predicted text can be determined using the text representation. For example, a language model can be used to predict one or more subsequent words based on the sequence of words in the text representation. The predicted text can be determined while audio input is being received. Further, the predicted text can be displayed with the text representation on the display unit. In particular, the predicted text can be displayed in real-time while audio input is being received at block  506 . 
     The predicted text can be accepted by the user based on detecting an end-point of the audio input. In some examples, the end-point can be detected once the user input of block  504  is no longer detected. In other examples, the end-point can be detected at a predetermined duration after one or more audio characteristics of the audio input no longer satisfy predetermined criteria. A determination can be made as to whether an end-point of the audio input is detected after displaying the predicted text. In accordance with a determination that an end-point of the audio input is detected after displaying the predicted text, the predicted text can be determined to be accepted by the user. In particular, the text representation and the accepted predicted text can be used to determine the primary user intent at block  510 . 
     In some examples, the one or more language models used to determine the text representation can be configured to recognize media-related terms in multiple languages. In particular, media-related terms (e.g., media titles, actor names, etc.) may have unique translations across different languages. For examples, the actor “Arnold Schwarzenegger” corresponds to “ ” in Chinese and “ ” in Hindi. The one or more language models used to determine the text representation can be trained using corpuses of media-related text in various languages. Thus, the one or more language models can be configured to recognize the corresponding translations of media-related terms in the various languages. 
     At block  510  of process  500 , a primary user intent corresponding to the media-related request can be determined. The primary user intent can be determined by performing natural language processing on the text representation. In particular, the text representation can be parsed and processed using a natural language processing module (e.g., natural language processing module  432 ) to determine multiple candidate user intents corresponding to the media-related request. The candidate user intents can be ranked according to probability and the candidate user intent having the highest probability can be determined to be the primary user intent. 
     Determining the primary user intent can include determining the relevant domain or actionable intent associated with the text representation. In some examples, a media type associated with the media-related request can be determined at block  510  and the relevant domain or actionable intent can be determined based on the determined media-type associated with the media-related request. For example, based on the media-related request “James Bond,” the media type can be determined to be “movies/television shows” and the corresponding actionable intent or domain can be determined to be “Find movies/television shows.” In this example, the media-related request can be fulfilled by perform a media search for “James Bond” in accordance with the media type “movies/television shows.” Specifically, a movies and television shows database can be searched for the media character “James Bond” to fulfill the media-related request. In another example, based on the media-related request “Taylor Swift,” the media type can be determined to be “music” and the corresponding actionable intent or domain can be determined to be “Find music.” In this example, the media-related request can be fulfilled by searching a music database (e.g., performing a search on the ITUNES music service) for the singer “Taylor Swift.” 
     In some examples, natural language processing for determining the primary user intent can be biased toward media-related user intents. In particular, the natural language processing module can be trained to identify media-related words and phrases (e.g., media titles, media genres, actors, MPAA film-rating labels, etc.) that trigger media-related nodes in the ontology. For example, the natural language processing module can identify the phrase “JURASSIC PARK” in the text representation as a movie title and as a result, trigger a “media search” node in the ontology associated with the actionable intent of searching for media items. In some examples, the biasing can be implemented by restricting the nodes in the ontology to a predetermined set of media-related nodes. For example, the set of media-related nodes can be nodes that are associated with the applications of the media device. Further, in some examples, the biasing can be implemented by weighting candidate user intents that are media-related more heavily than candidate user intents that are not media-related. 
     In some examples, the primary user intent can be obtained from a separate device (e.g., DA server  106 ). In particular, the audio data can be transmitted to the separate device to perform natural language processing. In these examples, the media device can indicate to the separate device (e.g., via data transmitted to the separate device with the sampled audio data) that the sampled audio data is associated with a media application. The indicating can bias the natural language processing toward media-related user intents. 
     The natural language processing module can be further trained to identify the semantics of media-related terms in various languages and regions. For example, the natural language processing module can recognize that “Arnold Schwarzenegger,” “   ” and “ ” all refer to the same actor. Additionally, movie titles may vary across different languages and regions. For example, the movie “Live Free or Die Hard” in the United States is titled as “Die Hard 4.0” in the United Kingdom. In another example, the movie “Top Gun” in the United States is titled as “Love in the Skies” in Isreal. Thus, the natural language processing module may be configured to identify that “Top Gun” in English and “Love in the Skies” in Hebrew both refer to the same movie. 
     In some examples, the natural language processing module can be configured to identify intended parameter values based on ambiguous terms in the media-related request. In particular, the natural language processing module can determine the strength of connection (e.g., relevance, salience, semantic similarity, etc.) between the ambiguous term and one or more parameter values. The parameter value having the strongest connection to the ambiguous term can be determined to be the intended parameter value. For example, the media-related request can be: “Show me the good ones.” The term “good” can be ambiguous as it does not explicitly define a particular parameter value. In this example, based on the strength of connection to the term “good,” the natural language processing module can determine that “good” refers to the parameter value of average user rating greater than a predetermined value. 
     In some examples, a preliminary user intent can be determined prior to determining the primary user intent. The preliminary user intent can include determining the actionable intent or domain using a portion of the audio input (but not the entire audio input) received at block  506 . The process for determining the preliminary user intent can be less robust and thus quicker than determining the primary user intent. This can enable the preliminary user intent to be determined while the audio input is still being received. Determining the preliminary user intent can enable data that is required to fulfill the media-related request to be pre-fetched, thereby reducing the response time of the digital assistant. For example, the media-related request can be: “What&#39;s on at 7 PM?” Based on the first portion of this request, “What&#39;s on . . . ,” the preliminary user intent can be determined to be “search channel programming.” Based on this preliminary user intent, data required to fulfill this preliminary user intent can be identified. In particular, it can be determined that the subscription information of the user would be needed to determine the channels available to the user. The programming corresponding to those channels can then be determined. The digital assistant can initially determine whether the required data is already stored on the media system or the digital assistant server. In accordance with a determination that the data is stored on the media system or the digital assistant server at the time the preliminary user intent is determined, the data can be retrieved while the primary user intent is being determined. In accordance with a determination that the data is not stored on the media system or digital assistant at the time the preliminary user intent is determined, the required data can be obtained while the primary user intent is being determined. For example, the digital assistant can automatically, without user intervention, communicate with the subscription service provider of the user and retrieve the channels that are available to the user. 
     As shown in  FIG. 5A , block  510  of process  500  can include one or more of blocks  512 - 518 . At block  512  of process  500 , a determination can be made as to whether the primary user intent comprises a user intent to narrow a primary media search query corresponding to primary set of media items  604 . In other words, it can be determined at block  510  whether the media-related request of block  506  is a request to narrow the previously received media search request. In some examples, determining whether the primary user intent comprises a user intent to narrow the primary media search query can include determining whether the media-related request includes a predetermined word or phrase corresponding to a user intent to narrow the primary media search query. The predetermined word or phrase can include one of a plurality of refinement terms. For example, the predetermined word or phrase can indicate an explicit request to narrow the previous media search request received prior to the media search request. Further, in some examples, the determination can be made based on the position of the predetermined word or phrase in the media-related request (e.g., at the beginning, middle, or end of the media-related request). 
     In the example shown in  FIGS. 6B-C , the media-related request may be: “Just the ones with Jack Ryan.” Text representation  615  corresponding to this media-related request can be parsed during natural language processing to determine whether the media-related request includes a predetermined word or phrase corresponding to a user intent to narrow the primary media search query. Examples of predetermined words or phrases that correspond to a user intent to narrow the primary media search query can include “just,” “only,” “filter by,” “which ones,” and the like. In this example, based on the predetermined word “just” positioned at the beginning of the media-related request, it can be determined that the primary user intent comprises a user intent to narrow the primary media search query corresponding to primary set of media items  604 . Specifically, it can be determined that the primary user intent is to narrow the search for action movies released in the last 10 years to include only media items with the character Jack Ryan. It should be recognized that other techniques can be implemented to determine whether the primary user intent comprises a user intent to narrow a primary media search query corresponding to primary set of media items  604 . Further, it should be recognized that the primary user intent can be based on one or more previous user intents corresponding to one or more previous media search requests received prior to the media search request of block  506 . 
     In accordance with the determination that the primary user intent comprises a user intent to narrow a primary media search query corresponding to primary set of media items  604 , one or more of blocks  520 - 534  can be performed. 
     At block  520  of process  500 , second primary set of media items  614  can be obtained to satisfy the primary user intent. Block  520  can include generating a second primary media search query corresponding to the primary user intent. The second primary media search query can be based on the media-related request (e.g., “Just the ones with Jack Ryan”) and the primary media search query (e.g., “Action movies from the last 10 years”). Specifically, the second primary media search query can include a set of parameter values. The set of parameter values can include one or more parameter values defined in the media-related request and one or more parameter values of the primary media search query. For example, the second primary media search query can be a query to search for media items having the media type of “movies,” the media genre of “action,” the release date of “last 10 years,” and the media character of “Jack Ryan.” Alternatively, the second primary media search query can be a query to filter primary set of media items  604  and identify only the media items within set of media items  604  having the media character of “Jack Ryan.” The second primary media search query can be generated by the natural language processing module (e.g., natural language processing module  432 ) based on the primary user intent. 
     Block  520  can further include performing the second primary media search query to obtain second primary set of media items  614 . The second primary media search query can be performed by searching one or more media databases for media items that satisfy the parameter value requirements of the second primary media search query. Each media item of the second primary set of media items can be associated with a set of parameter values. The set of parameter values can include one or more parameter values in the primary media search query and one or more parameter values defined in the media-related request of block  506 . Further, each media item of the second primary set of media items  614  can be associated with a relevancy score. The relevancy score can indicate the likelihood that the media item satisfies the primary user intent. For example, a higher relevancy score can indicate a higher likelihood that the media item satisfies the primary user intent. The second primary media search query can be performed by the task flow processing module (e.g., task flow processing module  436 ). 
     In examples where primary set of media items  604  are obtained by performing a string search based on the previously received media search request (e.g, received via a keyboard interface), the second primary media search query can be performed by searching primary set of media items  604  for media items that satisfy the parameter value requirements defined in the media-related request (e.g., “Jack Ryan”). In particular, the parameter values associated with primary set of media items  604  can be first obtained. The second primary set of media items  614  can then be obtained by performing a structured search using the obtained parameter values and based on the parameter values defined in the media-related request. 
     At block  522  of process  500 , second primary set of media items  614  can be displayed on the display unit via user interface  602 . In particular, as shown in  FIG. 6C , display of primary set of media items  604  on the display unit can be replaced with display of second primary set of media items  614 . Second primary set of media items  614  can be displayed according to the relevancy score associated with each media item. For example, with reference to  FIG. 6C , second primary set of media items  614  can be arranged in decreasing order of relevancy score from left to right on user interface  602 . 
     At block  524  of process  500 , additional sets of media items can be obtained. The additional sets of media items can be obtained to offer the user alternative options that may be pertinent to the primary user intent. As shown in  FIG. 5B , block  524  can include blocks  526 - 532 . 
     At block  526  of process  500 , a core set of parameter values associated with second primary set of media items  614  can be identified. The core set of parameter values can be identified from the set of parameter values in the second primary media search query. In particular, non-salient parameter values in the set of parameter values can be identified and disregarded. The remaining parameter values in the set of parameter values after disregarding non-salient parameter values can be identified as the core set of parameter values. Non-salient parameter values can be predetermined parameter values such as, for example, media release date ranges, media type, media provider, media quality rating, free or paid media, live or on-demand media, and the like. The core set of parameter values can have fewer parameter values than the set of parameter values. 
     In the example of  FIG. 6C , the set of parameter values in the second primary media search query includes the parameter values “action movie,” “last 10 years,” and “Jack Ryan.” In this example, the parameter value “last 10 years” can be identified as a non-salient parameter value (e.g., media release data range) and removed. Thus, the remaining parameter values “action movie” and “Jack Ryan” can be identified as the core set of parameter values. 
     At block  528  of process  500 , one or more additional parameter values can be identified. The one or more additional parameter values can be identified based on information that is likely to reflect the media consumption interests of the user. For example, the one or more additional parameter values can be identified based on the user&#39;s media selection history, the user&#39;s media search history, or the media items in the user&#39;s watch list. Additionally or alternatively, the one or more additional parameter values can be identified based on the media selection history of a plurality of users, which can indicate the parameter values of media items that are currently most popular among users of media devices. In some examples, methods of identifying one or more additional parameter values can be similar to methods of determining other relevant parameter values described at block  560 . 
     Returning to the example of  FIG. 6C , it can be determined that action movies starring Ben Affleck are popular among users of media devices. Further, it can be determined that the user recently searched for or selected movies starring Ben Affleck. Thus, in this example, “Ben Affleck” can be identified as a parameter value of the one or more additional parameter values. 
     At block  530  of process  500 , one or more additional media search queries can be generated. The additional media search queries can be based on the core set of parameter values identified at block  526 . Further, the additional media search queries can be based on the one or more additional parameter values identified at block  528 . For example, in  FIG. 6C , the one or more additional media search queries can include a search for action movies with Jack Ryan (core set of parameter values) and a search for action movies starring Ben Affleck (additional parameter value identified at block  528 ). 
     Blocks  526 - 530  can be performed by the natural language processing module (e.g., natural language processing module  432 ). In particular, the natural language processing module can identify the core set of parameter values (at block  526 ) and one or more additional media search queries (at block  528 ) to determine one or more additional user intents. The natural language processing module can then generate one or more additional media search queries (e.g., structured queries described above with reference to  FIG. 4B ) based on the one or more additional user intents. 
     At block  532  of process  500 , the one or more additional media search queries of block  530  can be performed. For example, the one or more additional media search queries can be performed by searching one or more media databases for media items that satisfy the additional media search queries. The media databases used can be based on the media type being searched. For example, a music database can be used for media search queries involving music and a movie/television show database can be used for media search queries involving music/television shows. One or more additional sets of media items  614  can thus be obtained from performing the one or more additional media search queries of block  530 . Specifically, in  FIG. 6C , additional set of media items  616  (e.g., the movies “Patriot Games,” “Clear and Present Danger,” etc.) can be obtained from searching for action movies with Jack Ryan and additional set of media items  618  (e.g., the movies “The Sum of All Fears,” “Daredevil,” etc.) can be obtained from searching for action movies starring Ben Affleck. Blocks  532  can be performed by the task flow processing module (e.g., task flow processing module  436 ). 
     It should be recognized that certain aspects of block  524 , described above, can similarly apply to blocks  546  or  562 . 
     At block  534  of process  500 , the one or more additional sets of media items can be displayed on the display unit. For example, as shown in  FIG. 6C , additional sets of media items  616  and  618  can be displayed via user interface  602 . Additional sets of media items  616  and  618  can serve to provide the user with additional options that are likely to interest the user. This can be desirable to increase the likelihood that the user will find and select a media item for consumption without having to request another search, which can reduce browsing time and improve user experience. 
     The manner in which the sets of media items are displayed can reflect the likelihood that the respective user intent corresponds to the user&#39;s actual intent. For example, as shown in  FIG. 6C , the second primary set of media items is associated with the primary user intent (the user intent that is most likely to reflect the actual user intent) and is displayed in a top row of user interface  602 . The one or more additional sets of media items  616  and  618  are associated with additional user intents (user intents that are less likely to reflect the actual user intent) and are displayed in one or more subsequent rows of user interface  602  below the top row. Further, the additional user intent associated with additional set of media items  616  can be more likely to reflect the actual user intent than the additional user intent associated with additional set of media items  618 . Thus, in this example, additional set of media items  618  can be displayed in the row below additional set of media items  616 . Although in the present example, the sets of media items are displayed in rows, it should be recognized that in other examples, other display configurations can be implemented. 
     With reference back to block  512 , in accordance with a determination that the primary user intent does not comprise a user intent to narrow the primary media search query, one or more of blocks  514 - 518 , or  536 - 548  can be performed. 
     At block  514  of process  500 , a determination can be made as to whether the primary user intent comprises a user intent to perform a new media search query. In some examples, the determination can be made based on explicit words or phrases in the media-related request. Specifically, it can be determined whether the media-related request includes a word or phrase corresponding to a user intent to perform a new media search query. The word or phrase can be predetermined words such as, “Show me,” “Find,” “Search for,” “Other movies with,” or the like. Further, in some examples, the determination can be made based on the position of the word or phrase in the media-related request (e.g., the beginning, middle, or end of the media-related request). In a specific example, the media-related request can be: “Show me some Jack Ryan movies.” Based on the words “Show me” at the beginning of this media-related request, it can be determined that the primary user intent is to perform a new media search query for movies with Jack Ryan. 
     In the absence of an explicit word or phrase indicating the user intent (e.g., “Show me,” “Find,” “Search for,” etc.), the determination at block  514  can be based on a word or phrase corresponding to a parameter value of one or more media items. For example, as shown in  FIG. 6D , the media-related request can be: “Jack Ryan” (represented by text  619 ). In this example, the media-related request does not include any explicit indication of whether the user intent is to narrow the primary media search query or to perform a new search. The digital assistant, however, may recognize that “Jack Ryan” corresponds to a parameter value of one or more media item. Specifically, it can be determined that “Jack Ryan” is a media character associated with several electronic books and movies. Based on these parameter values, the primary user intent can be determined to be performing a new media search query for electronic books and movies with the character Jack Ryan. Other examples of words or phrases corresponding to a parameter value of one or more media items can include “Tom Cruise,” “JURASSIC PARK,” “Spy movies,” “Sean Connery,” “Cartoons,” “FROZEN,” and the like. 
     In accordance with a determination that the primary user intent comprises a user intent to perform a new media search query, one or more of blocks  536 - 548  can be performed. At block  536  of process  500 , a third primary set of media items can be obtained in accordance with the primary user intent. Block  536  can be similar to block  520 . In particular, block  536  can include generating a third primary media search query based on the media-related request. The third primary media search query can correspond to the primary user intent of performing a new media search query. Specifically, the second primary media search query can include one or more parameter values defined in the media-related request. For example, with reference to  FIG. 6D , the third primary media search query generated can be a query to search for media items with the media character “Jack Ryan.” 
     Block  536  can further include performing the third primary media search query to obtain third primary set of media items  620 . The third primary media search query can be performed by searching one or more media databases for media items that satisfy the parameter value requirements of the third primary media search query. Each media item of third primary set of media items  620  can include one or more parameter values defined in the media-related request. Specifically, in the present example, each media item of third primary set of media items  620  can include “Jack Ryan” as a media character. 
     In some examples, the third primary media search query can be performed in accordance with the media type associated with the media-related request. As described above, the media type associated with the media-related request can be determined at block  510  while determining the primary user intent. The application or database used to perform the third primary media search query can be specific to the determined media type. In one example, if the media type is determined to be music, the third primary media search query can be performed using a music search application and/or a music database (e.g., ITUNES STORE application), and not, for example, a movies database. 
     In some examples, the media-related request can be associated with more than one media type. For example, the media-related request “FROZEN” can be associated with several media types, such as movies/television shows, music (e.g., the soundtrack), and electronic books. When performing the third primary media search query, a plurality of media items associated with various media types can be obtained from one or more media databases. Each media item can be associated with a relevancy score. The relevancy score can indicate how relevant the respective media item is with respect to the third primary media search query. Further, the relevancy score can be specific to the media database from which the candidate media item was obtained. In some examples, in order for media items from different databases to be compared based on the same standard, a normalized ranking of the plurality of candidate media items can be performed. In particular, the relevancy score can be normalized across the one or more media databases and the normalized relevancy score can be used to perform a normalized ranking of the candidate media items. For example, a universal media search application or database (e.g., spotlight of APPLE OS X or IOS) can be used to perform the third primary media search query. The universal media search application or database can be a service external to the digital assistant. Using the universal media search application or database, relevant media items can be obtained from various sources or databases (e.g., ITUNES STORE, APP STORE, IBOOKS, media items stored on the user&#39;s device, etc.) and the relevant media items can be ranked based on a normalized relevancy score. The media items can then be ordered and displayed according to the normalized ranking at block  540  for user selection. 
     The one or more databases used to obtain the third primary set of media items can include information derived from various sources. In some examples, the one or more databases can include information from one or more media critic reviews. The media critic reviews can be authored by, for example, professional media critics, journalists, bloggers, users of social media services or the like. In an illustrative example, the one or more media critic reviews can include a phrase such as “car chases” to describe movies such as “Bullitt,” “The Bourne Identity,” or “Fast Five.” The phrase “car chases” can be extracted from the one or more media critic reviews as a parameter value, and this parameter value can be associated with one or more of these movies in a media database. Thus, for the media-related request “Show me movies with good car chases,” the corresponding third primary media search query generated can be a search for movies with the parameter value “car chases.” In searching one or more databases, candidate media items such as “Bullitt,” “The Bourne Identity,” or “Fast Five” can thus be obtained. 
     In other examples, the one or more databases can include information derived from the closed captioning of various movies, videos, or television shows. In particular, one or more parameter values can be extracted based on the closed captioning. For example, the closed captioning of movies such as “Bullitt,” “The Bourne Identity,” or “Fast Five,” may include several instances of the caption “[Tire screeching]” to indicate the sound associated with a car chase. Based on this caption, one or more of these movies may be associated with the parameter value “car chase” in a media database. A candidate media item associated with this parameter value (e.g., “Bullitt,” “The Bourne Identity,” “Fast Five,” or the like) can thus be identified when performing the third primary media search query. 
     In some examples, the media-related request can be a media search request based on a media item on which user interface  602  is focused. For example, cursor  609  of user interface  602  can be positioned on media item  611  while the media-related request is received at block  506 . A determination can be made as to whether the media-related request is a request to obtain an alternative set of media items similar to media item  611 . In one example, the media-related request can be: “More like this.” In this example, it can be determined based on the context of the position of cursor  609  that “this” refers to media item  611 . Thus, it can be determined that the media-related request is a request to obtain an alternative set of media items similar to media item  611 . In response to determining that the media-related request is a request to obtain an alternative set of media items similar to media item  611 , the third primary set of media items can be obtained at block  536 , where each media item of the third primary set of media items includes one or more parameter values of media item  611 . For instance, in one example, media item  611  can be the foreign action movie “Crouching Tiger, Hidden Dragon.” In this example, the obtained third primary set of media items can include media items that share one or more parameter values of this movie. In particular, the obtained third primary set of media items can, for example, include movies that are directed by Ang Lee, include martial arts scenes, or star Chow Yun-Fat, Michelle Yeoh, or Zhang Ziyi. 
     It should be recognized that certain aspects of block  536  can similarly apply to blocks  520 ,  524 ,  546 ,  562 , or  566 . 
     At block  538  of process  500 , a determination can be made as to whether at least one media item corresponding to the third primary media search query can be obtained. Upon performing the third primary media search query at block  536 , the number of media items obtained (or that are obtainable) from the search query can be determined. If the number of media items obtained is one or more, then it can be determined that at least one media item corresponding to the third primary media search query can be obtained. For example, the third primary media search query for the media-related request “Jack Ryan,” can return at least the movies “Patriot Games,” and “Clear and Present Danger.” Thus, in this example, it can be determined that at least one media item corresponding to the third primary media search query can be obtained. In accordance with a determination that at least one media item corresponding to the third primary media search query can be obtained, block  540  can be performed. As will become evident in the description below, the determination at block  538  can be desirable to ensure that at least one media item is obtained for the third primary media search query performed at block  536 . This can prevent the situation where no media items are displayed for a media search request and can save the user the trouble of having to provide another media search request, which improves user experience. 
     At block  540  of process  500 , third primary set of media items  620  can be displayed on the display unit via user interface  602 . In particular, as shown in  FIG. 6E , display of primary set of media items  604  on the display unit can be replaced with display of third primary set of media items  620 . Block  540  can be similar to block  522 . Third primary set of media items  620  can be displayed according to the relevancy score associated with each media item. For example, with reference to  FIG. 6E , third primary set of media items  620  can be arranged in decreasing order of relevancy score from left to right on user interface  602 . 
     With reference back to block  538 , in some examples, it can be determined that at least one media item corresponding to the third primary media search query cannot be obtained. For example, the media-related request or the corresponding text representation from STT processing may define incorrect parameter values or parameter values that are different from those actually intended by the user. In one such example, as shown in  FIG. 6F , the media-related request may be “Jackie Chan and Chris Rucker” (represented by text  627 ). In this example, no media items may be obtained from performing the third primary media search query corresponding to this media-related request, and thus it can be determined that at least one media item corresponding to the third primary media search query cannot be obtained. In other examples, the media-related request may define incompatible parameters, such as “Jackie Chan” and “Spiderman,” or “Graphic violence” and “Suitable for young children.” In accordance with a determination that at least one media item corresponding to the third primary media search query cannot be obtained, block  542 - 548  can be performed to present the user with alternative results that are likely to satisfy the user&#39;s actual intent. 
     At block  542  of process  500 , the least pertinent parameter value of the third primary media search query can be identified. In particular, a salience score for each parameter value in the third primary media search query can be determined based on factors such as the popularity of media items having the parameter value, the frequency of occurrence of the parameter value in previous media search requests, or the frequency of occurrence of the parameter value in a population of media items. The least pertinent parameter value can be identified as the parameter value with the lowest salience score. For example, between the parameter values “Jackie Chan” and “Chris Rucker,” the parameter value “Chris Rucker” can have the lower salience score since Chris Rucker is a football athlete while Jackie Chan is popular actor. Thus Jackie Chan is associated with a greater number of media items and previous media search queries than Chris Rucker. Accordingly, in this example, the parameter value “Chris Rucker” can be determined to be the least pertinent parameter value. 
     At block  544  of process  500 , one or more alternative parameter values can be determined. The one or more alternative parameter values can be determined based on the identified least pertinent parameter value. For example, fuzzy string matching can be performed between the identified least pertinent parameter value and a plurality of media-related parameter values in a data structure. In particular, the parameter value in the data structure with the shortest edit distance within a predetermined threshold can be determined to be an alternative parameter value. For example, based on fuzzy string matching of the parameter value “Chris Rucker,” the parameter value “Chris Tucker” can be determined to have the shortest edit distance among a plurality of media-related parameter values in a data structure. Thus, in this example, “Chris Tucker” can be determined to be an alternative parameter value. 
     Additionally, or alternatively, one or more alternative parameter values can be determined based on the other parameter values in the third primary media search query (e.g., parameter values other than the least pertinent parameter value). In particular, parameter values closely related to the other parameter values in the third primary media search query can be determined. For example, it can be determined that parameter values such as “action movies” and “martial arts” are closely related to the parameter value “Jackie Chan,” based on the existence of multiple media items starring “Jackie Chan” that also have the parameter values of “action movies” and “martial arts. 
     At block  546  of process  500 , fourth primary set of media items can be obtained to satisfy the primary user intent. Block  546  can be similar to block  520 . In particular, one or more alternative primary media search queries can be generated. The one or more alternative primary search queries can be generated using the one or more alternative parameter values determined at block  544 . For example, in  FIGS. 6F-G , where the media-related request is “Jackie Chan and Chris Rucker” (represented by text  627 ) and the alternative parameter value is determined to be “Chris Tucker,” the alternative primary search query can be a search for media items with the parameter values “Jackie Chan” and “Chris Tucker.” Thus, in this example, the least pertinent parameter value can be replaced by an alternative parameter value that more likely reflects the actual intent of the user. The one or more alternative primary media search queries can then be performed to obtain fourth primary set of media items  628 . In the present example of searching for media items with parameter values “Jackie Chan” and “Chris Tucker,” fourth primary set of media items  628  can include movies, such as “RUSH HOUR,” “RUSH HOUR 2,” or “RUSH HOUR 3.” 
     At block  548  of process  500 , fourth primary set of media items  628  can be displayed on the display unit via user interface  602 . Block  548  can be similar to block  522 . In particular, as shown in  FIG. 6G , display of primary set of media items  604  on the display unit can be replaced with display of fourth primary set of media items  628 . 
     At block  550  of process  500 , a determination can be made as to whether one or more previous user intents exist. The one or more previous user intents can correspond to one or more previous media-related requests received prior to the media-related request of block  506 . An example of a previous media-related request can include the previously received media-related request corresponding to the primary media search query and primary set of media items  604  of block  502 . The determination can be made based on analyzing the history of previous user intents stored on the media device (e.g., media device  104 ) or a server (e.g., DA server  106 ). In some examples, only previous user intents within a relevant timeframe are taken into account when determining whether one or more previous user intents exist. The relevant time frame can refer to a predetermined timeframe prior to when the media-related request of block  506  is received. In other examples, the relevant time frame can be based on an interactive session with the digital assistant. In particular, the media-related request of block  506  can be part of an interactive session with the digital assistant that includes a sequence of media-related requests. In these examples, the relevant timeframe can be from the time at which the interactive session was initiated to the time at which the interactive session was terminated. A determination can be made as to whether the interactive session contains one or more previous media-related requests received prior to the media-related request of block  506 . If the interactive session contains one or more previous media-related requests, then it can be determined that one or more previous user intents exist. The one or more previous user intents and the primary user intent can thus be associated with the same interactive session with the digital assistant. Conversely, if the interactive session does not contain one or more previous media-related requests, then it can be determined that one or more previous user intents do not exist. In response to determining that one or more previous user intents exist, block  552  can be performed. Alternatively, in response to determining that one or more previous user intents do not exist, block  560  can be performed. 
     At block  552  of process  500 , one or more secondary user intents can be determined. The one or more secondary user intents can be determined based on the primary user intent of block  510  and the one or more previous user intents determined to exist at block  550 . Specifically, the one or more secondary user intents can include a combination of the primary user intent and the one or more previous user intents. In some examples, the one or more previous user intents can be determined based on the media-related request history of the user on the media device. 
     Returning to the example of  FIGS. 6D-E , the primary user intent can be the intent to search for media items with the character “Jack Ryan.” In one example, a first previous user intent can be the intent to search for action movies from the past 10 years. In addition, a second previous user intent can be the intent to search for media items starring Ben Affleck. The secondary user intents can thus be a combination of two or more of these user intents. In particular, one secondary user intent can be a combination of the primary user intent and the first previous user intent (e.g., the user intent to search for action movies with Jack Ryan from the past 10 years). Another secondary user intent can be a combination of the first previous user intent and the second previous user intent (e.g., the user intent to search for action movies starring Ben Affleck from the last 10 years). Block  552  can be performed using the natural language processing module (natural language processing module  432 ) of the media device. As shown in  FIG. 5D , block  552  can include blocks  554 - 560 . 
     At block  554  of process  500 , incorrect user intents among the one or more previous user intents can be identified. In particular, the one or more previous user intents can be analyzed to determine whether any incorrect user intents are included. A previous user intent can be determined to be incorrect if it is indicated, explicitly or implicitly, as being incorrect by a subsequent previous user intent. For example, the one or more previous user intents may include user intents corresponding to the following sequence of previous media-related requests: 
     [A] “Show me some James Bond movies.” 
     [B] “Just the ones with Daniel Smith.” 
     [C] “No, I meant Daniel Craig.” 
     In this example, based on the explicit phrase “No, I meant . . . ,” the previous user intent associated with request [C] can be determined to be an intent to correct the previous user intent associated with request [B]. Thus, in this example, the previous user intent associated with request [B] that precedes request [C] can be determined to be incorrect. It should be appreciated that in other examples, request [C] can implicitly indicate that request [B] is incorrect. For example, request [C] can alternatively be simply “Daniel Craig.” Based on the similarity of the strings “Daniel Craig” to “Daniel Smith” and the improved relevancy associated with the parameter value “Daniel Craig” as opposed to “Daniel Smith,” the previous user intent associated with request [C] can be determined to be an intent to correct the previous user intent associated with request [B]. 
     In other examples, a previous user intent can be determined to be incorrect based on a user selection of a media item that is inconsistent with the previous user intent. For example, a previous request can be: “Show me videos produced by Russell Simmons.” In response to this previous request, a primary set of media items including videos produced by Russell Simmons may have been displayed for user selection. Further, additional sets of media items relevant to the previous request may have been displayed with the primary set of media items. In this example, it can be determined that the user selected a media item in the additional sets of media items that was produced by “Richard Simmons” rather than “Russell Simmons.” Based on this user selection of a media item that was inconsistent with the previous user intent of searching for videos produced by Russell Simmons, it can be determined that the previous user intent is incorrect. In other words, it can be determined that the correct user intent should be searching for videos produced by “Richard Simmons” rather than “Russell Simmons.” 
     In accordance with a determination that the one or more previous user intents include incorrect previous user intents, the incorrect previous user intents may not be used to determine the one or more secondary user intents. In particular, the incorrect previous user intents may be excluded and thus may not be used to generate the combinations of user intents at block  556  for determining the one or more secondary user intents. However, in some examples, the corrected user intent can be used to generate the combination of user intents and determine the one or more secondary user intents. For instance, in the respective examples described above, the corrected previous user intent associated with “Daniel Craig” (e.g., searching for James Bond movies with Daniel Craig) and the corrected previous user intent associated with “Richard Simmons” (e.g., searching for videos produced by Richard Simmons) can be used to determine the one or more secondary user intents. 
     At block  556  of process  500 , a plurality of user intent combinations can be generated based on the primary user intent and the one or more previous user intents. In an illustrative example, the media device may have received the following sequence of media-related requests, where the primary user intent is associated with request [G] and the one or more previous user intents are associated with requests [D]-[F]. 
     [D] “Movies starring Keanu Reeves.” 
     [E] “Shows containing graphic violence.” 
     [F] “Movies suitable for young children” 
     [G] “Cartoons.” 
     In this example, the plurality of user intent combinations can include any combination of the primary user intent and the one or more previous user intents associated with requests [D] through [G]. One exemplary user intent combination can be a search for movies starring Keanu Reeves with graphic violence (e.g., combination based on requests [D] and [E]). Another exemplary user intent combination can be a search for cartoon movies that are suitable for young children (e.g., combination based on request [F] and [G]). 
     At block  558  of process  500 , incompatible user intent combinations can be excluded. In particular, the incompatible user intent combinations can be identified and the one or more secondary user intents may not be determined based on the identified incompatible user intent combinations. In some examples, an incompatible user intent combination may be a user intent combination that does not correspond to any media item. Specifically, for each user intent combination, a corresponding media search can be performed. If no media item is obtained for a particular media search, the corresponding user intent combination can be determined to be an incompatible user intent combination. For example, a user intent combination can be based on requests [E] and [F], described above. In this example, a corresponding media search for movies suitable for children that contain graphic violence can be performed. However, such a media search may not yield any media items. Thus, in this example, the user intent combination based on requests [E] and [F] can be determined to be an incompatible user intent combination. It should be appreciated that in other examples, different predetermined threshold values can be established for determining incompatible user intent combinations. For example, a user intent combination that does not correspond to greater than a predetermined number of media items can be determined to be incompatible. 
     In other examples, an incompatible user intent combination can be determined based on the parameter values associated with the user intent combination. In particular, certain parameter values can be predetermined to be incompatible. For example, the parameter value of “graphic violence” can be predetermined to be incompatible with the parameter value “suitable for young children.” Thus, a user intent combination containing two or more parameter values that are predetermined to be incompatible can be determined to be an incompatible user intent combination. Further, it can be predetermined that certain parameters require a singular value. For example, the parameters of “media title,” “media type,” and “MOTION PICTURE ASSOCIATION OF AMERICA film-rating” can each be associated with no more than one parameter value in a user intent combination. In particular, the combination of a first user intent for searching for movies and a second user intent for searching for songs would be an incompatible combination. Thus, a user intent combination can be determined to be incompatible if it contains more than one parameter value for a parameter predetermined to require a singular value. Incompatible user intent combinations can be excluded such that the combinations are not used to determine the one or more secondary user intents at block  552 . In particular, the one or more secondary user intents may not include any incompatible user intent combinations. Removing incompatible user intent combinations from consideration can be desirable to increase the relevance of media items displayed for user selection. 
     The one or more secondary user intents can be determined based on the remaining user intent combinations that were not determined to be incompatible. In particular, the user intents of each remaining user intent combination can be merged to generate the one or more secondary user intents. Further, each of the remaining user intent combinations can be associated with at least one media item (or at least a predetermined number of media items). In some examples, the one or more secondary intents can include the one or more remaining user intent combinations. 
     Returning back to the example with requests [D]-[G] described above, a secondary user intent of the one or more secondary user intents can include a combination of the primary user intent (e.g., primary user intent associated with request [G]) and a previous user intent of the one or more previous user intents (e.g., previous user intent associated with request [F]). For example, the secondary user intent can be a media search for cartoon movies that are suitable for young children. Additionally, a secondary user intent of the one or more secondary user intents can include a combination of two or more previous user intents of the one or more previous user intents (e.g., previous user intent associated with requests [D] and [E]). For example, the secondary user intent can be a media search for movies with graphic violence starring Keanu Reeves. 
     At block  560  of process  500 , one or more secondary user intents can be generated based on other relevant parameter values. The one or more secondary user intents determined at block  560  can be in addition to, or alternative to, the one or more secondary intents determined at block  552 . The other relevant parameter values may be based on information other than the media search history of the user on the media device. In particular, the information used to determine the other relevant parameter values can reflect the media interests and habits of the user, and thus can reasonably predict the actual intent of the user. 
     In some examples, the other relevant parameter values can be based on the media selection history of the user on the media device. In particular, the other relevant parameter values can include parameter values associated with media items previously selected by the user for consumption (e.g., selected prior to receiving the media-related request at block  506 ). In some examples, the other relevant parameter values can be based on the media watch list of the user on the media device. The media watch list can be a user-defined list of media items that the user is interested in or wishes to consume in the near future. Parameter values associated with the user selection history or the user media watch list can thus reflect the media interests or habits of the user. In some examples, the other relevant parameters can be based on the media search history of the user on a device external to the media device. In particular, the history of media-related searches performed on an external media device (e.g., user device  122 ), can be obtained from the external media device. These media-related searches can be web searches, ITUNES store searches, local media file searches on the device, or the like. The other relevant parameter values can thus include parameter values derived from the media-related search history of the external media device. 
     In some examples, the other relevant parameter values can be based on a media item on which the user interface is focused. For example, with reference to  FIG. 6A , cursor  609  can be on media item  611  while the media-related request is received at block  506 . Thus, it can be determined that the focus of user interface  602  is on media item  611  while the media-related request is received at block  506 . In this example, the other relevant parameter values can be contextually-related to media item  611 . Specifically, the other relevant parameter values can include one or more parameter values of media item  611 . In some examples, the other relevant parameter values can be based on text associated with the media items displayed on the display unit while the media-related request is received at block  506 . For example, in  FIG. 6A , a plurality of text associated with primary set of media items  604  and secondary sets of media items  606  can be displayed on the display unit while the media-related request is received at block  506 . The plurality of text can describe parameter values of the associated media items. The other relevant parameter values can thus include one or more parameter values described by the plurality of text. 
     It should be recognized that other information internal or external to the media device can be used to determine the other relevant parameter values. For instance, in some examples, the other relevant parameter values can be determined in a similar manner as the additional parameter values identified at block  528 . 
     A ranking score can be determined for each of the one or more secondary user intents of blocks  552  and  560 . The ranking score can represent the likelihood that the secondary user intent corresponds to the actual user intent of the user. In some examples, a higher ranking score can represent a higher likelihood that the respective secondary user intent corresponds to the actual user intent. As described below, the ranking score can be determined based on similar information used to derive the one or more secondary user intents. 
     In some examples, the ranking score for each of the one or more secondary user intents can be determined based on the media-related request history (e.g., media search history) of the user or of a plurality of users. In particular, the ranking score can be determined based on the time and the order in which each of the media-related requests and the one or more previous media-related requests were received. Secondary user intents that are based on the more recently received media search request can be more likely to have a higher ranking score than secondary user intents that are based on the earlier received media-related request. For instance, in the above described example of requests [D]-[G], request [G] can be the most recently received media-related request, whereas request [D] can be the earliest received media-related request. In this example, a secondary user intent based on request [G] can be more likely to have a higher ranking score than a secondary user intent based on request [D]. 
     Further, the ranking score can be based on the frequency of occurrence of the parameter values in the media-related request history of the user or of a plurality of users. For example, if the parameter value “Keanu Reeves” occurs more frequently than the parameter value “graphic violence” in the media-related request history of the user or the media-related request history of a plurality of users, then secondary user intents containing the parameter value “Keanu Reeves” can be more likely to have a higher ranking score than secondary user intents containing the parameter value “graphic violence.” 
     In some examples, the ranking score for each of the one or more secondary user intents can be determined based on a selection history of the user or a plurality of users. The user selection history can include a list of media items that were previously selected by the user or the plurality of users for consumption. Secondary user intents that include the parameter values of one or more previously selected media items can be more likely to have a higher ranking score than secondary user intents that do not include the parameter values of any previously selected media item. In addition, secondary user intents that include the parameter values of a more recently selected media item can be more likely to have a higher ranking score than secondary user intents that include the parameter values of an earlier selected media item. Further, secondary user intents having parameter values that occur more frequently among previously selected media items can be more likely to have a higher ranking score than secondary user intents having parameter values that occur less frequently among previously selected media items. 
     In some examples, the ranking score for each of the one or more secondary user intents can be determined based on a media watch list of the user or a plurality of users. For example, secondary user intents that include the parameter values of one or more media items on the media watch list can be more likely to have a higher ranking score than secondary user intents that do not include the parameter values of any media items on the media watch list. 
     At block  562  of process  500 , one or more secondary sets of media items can be obtained. Block  562  can be similar to block  520 . In particular, one or more secondary media search queries corresponding to the one or more secondary user intents of blocks  552  and/or  560  can be generated. The one or more secondary media search queries can be performed to obtain one or more secondary sets of media items  622 . For example, with reference back to  FIG. 6E , a first secondary media search query for action movies with Jack Ryan from the last 10 years can be generated and performed to obtain secondary set of media items  624 . Additionally, a second secondary media search query for action movies starring Ben Affleck from the last 10 years can be generated and performed to obtain secondary set of media items  626 . 
     At block  564  of process  500 , the one or more secondary sets of media items can be displayed on the display unit. Block  564  can be similar to block  534 . As shown in  FIG. 6E , third primary set of media items  620  can be displayed at a top row of user interface  602 . The secondary sets of media items  624  and  626  can be displayed in subsequent rows of user interface  602  below the top row. Each row of the subsequent rows can correspond to a secondary user intent of the one or more secondary user intents of block  552  and/or  560 . 
     The one or more secondary sets of media items can be displayed in accordance with the ranking scores of the corresponding one or more secondary user intents. In particular, the secondary sets of media items corresponding to secondary user intents with higher ranking scores can be displayed more prominently (e.g., in a higher row closer to the top row) than the secondary sets of media items corresponding to secondary user intents with lower ranking scores. 
     With reference back to block  510 , in accordance with a determination that the primary user intent does not comprise a user intent to perform a new media search query, one or more of blocks  516 - 518  can be performed. At block  516  of process  500 , a determination can be made as to whether the primary user intent comprises a user intent to correct a portion of the primary media search query. The determination can be made based on an explicit word or phrase indicating a user intent to correct a portion of the primary media search query. Specifically, it can be determined whether the media-related request includes a predetermined word or phrase indicating a user intent to correct a portion of the primary media search query. For example, with reference to  FIGS. 6H-I , the media-related request can be: “No, I meant adventure movies” (represented by text  635 ). In this example, based on the explicit phrase “No, I meant . . . ” occurring at the beginning of the media-related request, it can be determined that the primary user intent comprises a user intent to correct a portion of the primary media search query. Specifically, the primary user intent can be determined to be a user intent to correct the primary media search query from searching for action movies from the last 10 years to searching for adventure movies from the last 10 years. Other examples of predetermined words or phrases indicating a user intent to correct a portion of the primary media search query can include “no,” “not,” “I mean,” “wrong,” or the like. 
     In other examples, the determination at block  516  can be made based on a similarity between a parameter value in the media-related request and a parameter value in the primary media search query. For instance, in one example, the previously received media-related request associated with the primary media search query can be: “Jackie Chan and Chris Rucker” and the media-related request can be: “Chris Tucker.” Based on the determined edit distance between the parameter values “Chris Rucker” and “Chris Tucker” being less than a predetermined value, it can be determined that the primary user intent comprises a user intent to correct the parameter value “Chris Rucker” in the primary media search query to “Chris Tucker.” Additionally or alternatively, the sequence of phonemes representing “Chris Rucker” and “Chris Tucker” can be compared. Based on the sequence of phonemes representing “Chris Rucker” being substantially similar to the sequence of phonemes representing “Chris Tucker,” it can be determined that the primary user intent comprises a user intent to correct “Chris Rucker” in the primary media search query to “Chris Tucker.” 
     Further, the salience of the parameter value “Chris Rucker” can be compared to the salience of the parameter value “Chris Tucker” with respect to the parameter value “Jackie Chan.” In particular, a media search can be performed using the parameter value “Jackie Chan” to identify a set of media items related to Jackie Chan. The salience of “Chris Rucker” and “Chris Tucker” with respect to “Jackie Chan” can be based on the number of media items among the set of media items related to Jackie Chan that are associated with each of the two parameter values. For example, “Chris Tucker” can be determined to be associated with significantly more media items among the set of media items related to Jackie Chan than “Chris Rucker.” Thus, the salience of “Chris Tucker” can be determined to be significantly more than the salience of “Chris Rucker” with respect to “Jackie Chan.” Based on this compared salience, it can be determined that the primary user intent comprises a user intent to correct “Chris Rucker” in the primary media search query. 
     In accordance with a determination that the primary user intent comprises a user intent to correct a portion of the primary media search query, the previous user intent associated with the primary media search query can be removed from consideration when determining one or more secondary user intents (e.g., block  552 ) associated with the media-related request. For example, the previous user intent associated with the previously received media-related request of “Jackie Chan and Chris Rucker” can be removed from consideration when determining one or more secondary user intents. Instead, the user intent associated with the corrected media-related request “Jackie Chan and Chris Tucker” can be considered when determining one or more secondary user intents. 
     Additionally, in accordance with a determination that the primary user intent comprises a user intent to correct a portion of the primary media search query, one or more of blocks  566 - 568  can be performed. At block  566  of process  500 , the fifth primary set of media items ( 628  or  636 ) can be obtained. Block  566  can be similar to block  520 . In particular, a fifth primary media search query corresponding to the primary user intent can be generated. The fifth primary media search query can be based on the media-related request and the primary media search query. Specifically, the portion of the primary media search query can be corrected in accordance with the media-related request to generate the fifth primary media search query. Returning to the example where the primary media search query is to search for media items starring “Jackie Chan” and “Chris Rucker” and the media-related request is “Chris Tucker,” the primary media search query can be corrected to generate the fifth primary media search query of searching for media items starring “Jackie Chan” and “Chris Tucker.” The fifth primary media search query can then be performed to obtain a fifth primary set of media items. 
     At block  568  of process  500 , the fifth primary set of media items ( 628  or  636 ) can be displayed on the display unit via a user interface (e.g., user interface  602 ). In particular, the display of the primary set of media items (e.g., primary set of media items  604 ) can be replaced with the display of the fifth primary set of media items ( 628  or  636 ). Block  540  can be similar to block  522 . Further, in some examples, blocks  550 - 564  can be performed to obtain and display one or more secondary set of media items ( 628  or  636 ) with the fifth primary set of media items to provide the user with additional options. 
     With reference back to  510 , in accordance with a determination that the primary user intent does not comprise a user intent to correct a portion of the primary media search query, block  518  can be performed. At block  518  of process  500 , a determination can be made as to whether the primary user intent comprises a user intent to change a focus of the user interface (e.g., user interface  602 ) displayed on the display unit. The user interface can include a plurality of media items. In some examples, the determination at block  518  can be made based on an explicit word or phrase in the media-related request that corresponds to a user intent to change a focus of the user interface. In one example, with reference to  FIG. 6J , the media-related request can be: “Go to THE DARK KNIGHT” (represented by text  644 ). In this example, it can be determined that the phrase “Go to . . . ” is a predetermined phrase corresponding to a user intent to change a focus of the user interface. Other examples of predetermined words or phrases that correspond to a user intent to change a focus of a user interface can include “Select,” “Move to,” “Jump to,” “Play,” “Buy,” or the like. Based on the predetermined word or phrase, it can be determined that the primary user intent comprises a user intent to change a focus of the user interface. 
     In other examples, the determination at block  518  can be made implicitly based on text corresponding to the media items displayed in the user interface. For example, with reference to  FIG. 6A , media items  604  and  606  can be associated with text describing one or more parameter values of media items  604  and  606 . In particular, the text can describe parameter values of media items  604  and  606 , such as the media title, the actors, the release date, or the like. As described above, at least a portion of this text can be displayed on user interface  602  in connection with the respective media items. The determination at block  518  can be made based on this text describing one or more parameter values of media items  604  and  606 . In the present example, media item  613  can be the movie “THE DARK KNIGHT” and the text can include the media title “THE DARK KNIGHT” associated with media item  613 . Based on a determination that the parameter value “THE DARK KNIGHT” defined in the media-related request matches the media title “THE DARK KNIGHT” of the text associated with media item  613 , it can be determined that the primary user intent comprises a user intent to change a focus of user interface  602  from media item  611  to media item  613 . It should be recognized that in some examples, the displayed text may not include all the parameter values of media items displayed via user interface  602 . In these examples, the determination at block  518  can be also based on parameter values of displayed media items that are not described in the displayed text. 
     In accordance with a determination that the primary user intent comprises a user intent to change a focus of the user interface, block  570  can be performed. At block  570  of process  500 , a focus of the user interface can be changed from a first media item to a second media item. For example, with reference to  FIG. 6K , the position of cursor  609  of user interface  602  can be changed from media item  611  to media item  613 . In some examples, changing the focus of user interface  602  can include selecting a media item. For example, media item  613  can be selected at block  570 . Selecting media item  613  can cause information associated with media item  613  to be displayed (e.g., movie preview information). Additionally or alternatively, selecting media item  613  can cause media content associated with media item  613  to be played on the media device and displayed on the display unit. 
     Although certain blocks of processes  500  are described above as being performed by a device or system (e.g., media device  104 , user device  122 , or digital assistant system  400 ), it should be recognized that in some examples, more than one device can be used to perform a block. For example, in blocks where a determination is made, a first device (e.g., media device  104 ) can obtain the determination from a second device (e.g., server system  108 ). Thus, in some examples, determining can refer to obtaining a determination. Similarly, in blocks where content, objects, text, or user interfaces are displayed, a first device (e.g., media device  104 ) can cause the content, objects, text, or user interfaces to be displayed on a second device (e.g., display unit  126 ). Thus, in some examples, displaying can refer to causing to display. 
     Further, it should be recognized that, in some examples, items (e.g., media items, text, objects, graphics, etc.) that are displayed in a user interface can also refer to items that are included in the user interface, but not immediately visible to the user. For example, a displayed item in a user interface can become visible to the user by scrolling to a suitable region of the user interface. 
     5. Electronic Devices 
     In accordance with some examples,  FIG. 7  shows a functional block diagram of an electronic device  700  configured in accordance with the principles of various described examples to, for example, provide voice control of media playback and real-time updating of virtual assistant knowledge. The functional blocks of the device can be 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. 7  can be 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. 7 , electronic device  700  can include input unit  703  configured to receive user input, such as tactile input, gesture input, and text input (e.g., remote control  124 , or the like), audio receiving unit  704  configured to receive audio data (e.g., microphone  272 , or the like), speaker unit  706  configured to output audio (e.g., speakers  268 , or the like), and communication unit  707  (e.g., communication subsystem  224 , or the like) configured to send and receive information from external devices via a network. In some examples, electronic device  700  can optionally include a display unit  702  configured to display media, user interfaces, and other content (e.g., display unit  126 , or the like). In some example, display unit  702  can be external to electronic device  700 . Electronic device  700  can further include processing unit  708  coupled to input unit  703 , audio receiving unit  704 , speaker unit  706 , communication unit  707 , and optionally display unit  702 . In some examples, processing unit  708  can include display enabling unit  710 , detecting unit  712 , determining unit  714 , audio receiving enabling unit  716 , obtaining unit  718 , identifying unit  720 , receiving unit  722 , excluding unit  724 , and generating unit  726 . 
     In accordance with some embodiments, processing unit  708  is configured to display (e.g., with display enabling unit  710 ) a primary set of media items on a display unit (e.g., with display unit  702  or a separate display unit). Processing unit  708  is further configured to detect (e.g., with detecting unit  712 ) a user input. Processing unit  708  is further configured to, in response to detecting a user input, receive audio input (e.g., with audio receiving enabling unit  716 ) at audio receiving unit  704 . The audio input contains a media-related request in natural language speech form. Processing unit  708  is further configured to determine (e.g., with determining unit  714 ) a primary user intent corresponding to the media-related request. Processing unit  708  is further configured to determine (e.g., with determining unit  714 ) whether the primary user intent comprises a user intent to narrow a primary media search query corresponding to the primary set of media items. Processing unit  708  is further configured to, in accordance with a determination that the primary user intent comprises a user intent to narrow the primary media search query, generate (e.g., with obtaining unit  718 ), based on the media-related request and the primary media search query, a second primary media search query that corresponds to the primary user intent, perform (e.g., with obtaining unit  720 ) the second primary media search query to obtain a second primary set of media items. Processing unit  708  is further configured to replacing display of the primary set of media items on the display unit with display of the second primary set of media items (e.g., with display enabling unit  710 ). 
     In some examples, determining whether the primary user intent comprises a user intent to narrow the primary media search query comprises determining whether the media-related request includes a word or phrase corresponding to a user intent to narrow the primary media search query. 
     In some examples, the second primary media search query includes one or more parameter values defined in the media-related request and one or more parameter values of the primary media search query. In some examples, the second primary set of media items is obtained based on the primary set of media items. 
     In some examples, the second primary media search query includes a set of parameter values. Processing unit  708  is further configured to identify (e.g., with identifying unit  720 ) a core set of parameter values from the set of parameter values, the core set of parameter values having fewer parameter values than the set of parameter values. Processing unit  708  is further configured to generate (e.g., with obtaining unit  718 ) one or more additional media search queries based on the core set of parameter values. Processing unit  708  is further configured to perform (e.g., with obtaining unit  718 ) the one or more additional media search queries to obtain one or more additional sets of media items. Processing unit  708  is further configured to display (e.g., with display enabling unit  710 ) the one or more additional sets of media items on the display unit. 
     In some examples, processing unit  708  is further configured to identify (e.g., with identifying unit  720 ) one or more additional parameter values based on a media selection history of a plurality of users. The one or more additional media search queries are generated using the one or more additional parameter values. 
     In some examples, the second primary set of media items is displayed at a top row of a user interface on the display unit and the one or more additional sets of media items are displayed at one or more subsequent rows of the user interface on the display unit. 
     In some examples, processing unit  708  is further configured to, in accordance with a determination that the primary user intent does not comprise a user intent to narrow the primary media search query, determine (e.g., with determining unit  714 ) whether the primary user intent comprises a user intent to perform a new media search query. Processing unit  708  is further configured to, in accordance with a determination that the primary user intent comprises a user intent to perform a new media search query, generate (e.g., with obtaining unit  718 ), based on the media-related request, a third primary media search query that corresponds to the primary user intent, determine (e.g., with determining unit  714 ) whether at least one media item corresponding to the third primary media search query can be obtained. Processing unit  708  is further configured to, in accordance with a determination that at least one media item corresponding to the third primary media search query can be obtained, perform (e.g., with obtaining unit  718 ) the third primary media search query to obtain a third primary set of media items and replace display of the primary set of media items on the display unit with display of the third primary set of media items (e.g., with display enabling unit  710 ). 
     In some examples, determining whether the primary user intent comprises a user intent to perform a new media search query further comprises determining whether the media-related request includes a word or phrase corresponding to a user intent to perform a new media search query. In some examples, determining whether the primary user intent comprises a user intent to perform a new media search query further comprises determining whether the media-related request includes a word or phrase corresponding to a parameter value of one or more media items. 
     In some examples, processing unit  708  is further configured to perform (e.g., with obtaining unit  718 ) the third primary media search query includes performing a normalized ranking of a plurality of candidate media items, where the plurality of candidate media items comprising a plurality of media types. 
     In some examples, determining the primary user intent includes determining a media type associated with the media-related request, where the third primary media search query is performed in accordance with the determined media type. 
     In some examples, performing the third primary media search query comprises identifying a candidate media item associated with a parameter value that is included in one or more media critic reviews of the identified candidate media item. 
     In some examples, performing the third primary media search query comprises identifying a candidate media item associated with a parameter value that is derived from closed captioning information of the identified candidate media item. 
     In some examples, processing unit  708  is further configured to, in accordance with a determination that no media items correspond to the third primary media search query, identify (e.g., with identifying unit  720 ) a least pertinent parameter value of the third primary media search query. Processing unit  708  is further configured to determine (e.g., with determining unit  714 ), based on the identified least pertinent parameter value, one or more alternative parameter values. Processing unit  708  is further configured to perform (e.g., with obtaining unit  718 ), using the one or more alternative parameter values, one or more alternative primary media search queries to obtain a fourth primary set of media items. Processing unit  708  is further configured to replacing display of the primary set of media items on the display unit with display of the fourth primary set of media items (e.g., with display enabling unit  710 ). 
     In some examples, processing unit  708  is further configured to, in accordance with a determination that the primary user intent does not comprise a user intent to narrow the primary media search query, determine (e.g., with determining unit  714 ) one or more secondary user intents based on the primary user intent and one or more previous user intents, the one or more previous user intents corresponding to one or more previous media-related requests received prior to the media-related request. Processing unit  708  is further configured to generate (e.g. with obtaining unit  718 ), one or more secondary media search queries that correspond to the one or more secondary user intents. Processing unit  708  is further configured to perform (e.g., with obtaining unit  718 ) the one or more secondary media search queries to obtain one or more secondary sets of media items. Processing unit  708  is further configured to display (e.g., with display enabling unit  710 ) the one or more secondary sets of media items on the display unit. 
     In some examples, the one or more previous media-related requests include a previous media-related request corresponding to the primary set of media items. 
     In some examples, processing unit  708  is further configured to determine (e.g., with determining unit  714 ) one or more combinations of the primary user intent and the one or more previous user intents, where each of the one or more combinations is associated with at least one media item, and where the one or more secondary intents comprise the one or more combinations. 
     In some examples, the one or more previous user intents and the primary user intent are associated with a same interactive session with the digital assistant. In some examples, the one or more secondary user intents are generated based on a media search history of a user on the one or more electronic devices. In some examples, the one or more secondary user intents are generated based on a media selection history of a user on the one or more electronic devices, the media selection history. 
     In some examples, processing unit  708  is further configured to receive (e.g., with receiving unit  722 ) a media search history from a second electronic device (e.g., via communication unit). The one or more secondary user intents are generated based on the media search history received from the second electronic device. 
     In some examples, the one or more secondary user intents are generated based on a media watch list of a user on the one or more electronic devices. In some examples, a plurality of text is displayed on the display unit while receiving the audio input, the plurality of text is associated with a plurality of media items displayed on the display unit while receiving the audio input, and the one or more secondary user intents are generated based on the displayed plurality of text. 
     In some examples, processing unit  708  is further configured to determine (e.g., with determining unit  714 ) a ranking score for each of the one or more secondary user intents, where the one or more secondary sets of media items are displayed in accordance with the ranking score for each of the one or more secondary user intents. 
     In some examples, the ranking score for each of the one or more secondary user intents is based on a time at which each of the media-related requests and the one or more previous media-related requests was received. In some examples, the ranking score for each of the one or more secondary user intents is based on a media search history of a user on the one or more electronic devices. In some examples, the ranking score for each of the one or more secondary user intents is based a media selection history of a user on the one or more electronic devices. In some examples, the ranking score for each of the one or more secondary user intents is based on a media watch list of a user on the one or more electronic devices. 
     In some examples, processing unit  708  is further configured to, in accordance with a determination that the primary user intent does not comprise a user intent to perform a new media search query, determine (e.g., with determining unit  714 ) whether the primary user intent comprises a user intent to correct a portion of the primary media search query. Processing unit  708  is further configured to, in accordance with a determination that the primary user intent comprises a user intent to correct a portion of the primary media search query, generate (e.g., with obtaining unit  718 ), based on the media-related request and the primary media search query request, a fifth primary media search query that corresponds to the primary user intent. Processing unit  708  is further configured to perform (e.g., with obtaining unit  718 ) the fifth primary media search query to obtain a fifth primary set of media items. Processing unit  708  is further configured to replace display of the primary set of media items on the display unit with display of the fifth primary set of media items (e.g., with display enabling unit  710 ). 
     In some examples, determining whether the primary user intent comprises a user intent to correct a portion of the primary media search query comprises determining whether the media-related request includes a word or phrase corresponding to a user intent to correct a portion of the primary media search query. In some examples, determining whether the primary user intent comprises a user intent to correct a portion of the primary media search query comprises determining whether a sequence of phonemes representing a portion of the media-related request is substantially similar to a sequence of phonemes representing a portion of a previous media-related request that corresponds to the primary media search query. 
     In some examples, generating the fifth primary media search query comprises identifying a set of media items associated with a portion of the primary media search query that is not to be corrected, where the fifth primary media search query is generated based on one or more parameter values of the set of media items associated with the portion of the primary media search query that is not to be corrected. 
     In some examples, processing unit  708  is further configured to, in accordance with a determination that the primary user intent comprises a user intent to correct a portion of the primary media search query, excluding (e.g., with excluding unit  724 ) the primary media search query from consideration when determining a secondary user intent corresponding to the media-related request. 
     In some examples processing unit  708  is further configured to, in accordance with a determination that the primary user intent does not comprise a user intent to correct a portion of the primary media search query, determine (e.g., with determining unit  714 ) whether the primary user intent comprises a user intent to change a focus of a user interface displayed on the display unit, wherein the user interface includes a plurality of media items. Processing unit  708  is further configured to, in accordance with a determination that the primary user intent comprises a user intent to change a focus of a user interface displayed on the display unit, change (e.g., with display enabling unit  710 ) a focus of the user interface from a first media item of the plurality of media items to a second media item of the plurality of media items. 
     In some examples, determining whether the primary user intent comprises a user intent to change a focus of a user interface displayed on the display unit comprises determining whether the media-related request includes a word or phrase corresponding to a user intent to change a focus of a user interface displayed on the display unit. 
     In some example, the user interface includes a plurality of text corresponding to the plurality of media items in the user interface, and wherein the determination of whether the primary user intent comprises a user intent to change a focus of a user interface displayed on the display unit is based on the plurality of text. 
     In some examples, processing unit  708  is further configured to determine (e.g., with determining unit  714 ) a text representation of the media-related request and display (e.g., with displaying enabling unit  710 ) the text representation on the display unit. In some examples, the text representation is determined using one or more language models. In some examples, the one or more language models are biased towards media-related text results. In some examples, the one or more language models are configured to recognize media-related text in multiple languages. 
     In some examples, a plurality of media items and text associated with the plurality of media items are displayed on the display unit. Processing unit  708  is further configured to generate (e.g., with generating unit  726 ) a second language model using the text associated with the plurality of media items, where the text representation is determined using the second language model. 
     In some examples, processing unit  708  is further configured to determine (e.g., with determining unit  714 ), using the text representation, a predicted text and display (e.g., with display enabling unit  710 ), on the display unit, the predicted text with the text representation. 
     In some examples, the predicted text is determined based on text displayed on the display unit while receiving the audio input. 
     In some examples, processing unit  708  is further configured to, determine (e.g., with determining unit  714 ) whether an end-point of the audio input is detected after displaying the predicted text, where in accordance with a determination that an end-point of the audio input is detected after displaying the predicted text, the text representation and the predicted text is used to determine the primary user intent. 
     In some examples, processing unit  708  is further configured to, while receiving the audio input, determine (e.g., with determining unit  714 ) a preliminary user intent based on a received portion of the audio input, identify (e.g., with identifying unit  720 ) data that is required to fulfill the preliminary user intent, determine (e.g., with determining unit  714 ) whether the data is stored on the one or more electronic devices at a time the preliminary user intent is determined, and in accordance with a determination that the data is not stored on the one or more electronic devices at the time the preliminary user intent is determined, obtain (e.g., with obtaining unit  718 ) the data. 
     In accordance with some embodiments, processing unit  708  is configured to receive (e.g., at input unit  703  or audio receiving unit  704 , and using receiving unit  722  or audio receiving enabling unit  716 ), from a user, a media search request in natural language speech form. Processing unit  708  is further configured to determine (e.g., with determining unit  714 ) a primary user intent corresponding to the media search request, obtaining a primary set of media items in accordance with the primary user intent. Processing unit  708  is further configured to determine (e.g., with determining unit  714 ) whether one or more previous user intents exist, where the one or more previous user intents corresponds to one or more previous media search requests received prior to the media search request. Processing unit  708  is further configured to, in response to determining that one or more previous user intents exist, determine (e.g., with determining unit  714 ) one or more secondary user intents based on the primary user intent and the one or more previous user intents. Processing unit  708  is further configured to obtain (e.g., with obtaining unit  718 ) a plurality of secondary sets of media items, wherein each secondary set of media items corresponds to a respective secondary user intent of the one or more secondary user intents. Processing unit  708  is further configured to display (e.g., with display enabling unit  710 ) the primary set of media items and the plurality of secondary sets of media items. 
     In some examples, determining the primary user intent further comprises determining whether the media search request contains an explicit request to narrow a previous media search request received prior to the media search request, where in accordance with a determination that the media search request contains an explicit request to narrow the previous media search request. The primary user intent is determined from the media search request and at least one of the one or more previous user intents. 
     In some examples, in response to determining that the media search request does not contain an explicit request to narrow the previous media search request, the primary user intent is determined from the media search request. 
     In some examples, the media search request is part of an interactive session with the digital assistant. Determining whether one or more previous user intents exist further comprises determining whether the interactive session includes one or more previous media search requests received prior to the media search request, wherein the one or more previous media search requests correspond to one or more previous user intents. In accordance with a determination that the interactive session contains one or more previous media search requests received prior to the media search request, a determination is made that one or more previous user intents. In accordance with a determination that the interactive session does not contain one or more previous media search requests received prior to the media search request, a determination is made that one or more previous user intents do not exist. 
     In some examples, processing unit  708  is further configured to, in response to determining that one or more previous media user intents do not exist, display (e.g., with display enabling unit  710 ) the primary set of media items. 
     In some examples, a secondary user intent of the one or more secondary user intents include a combination of the primary user intent and a previous user intent of the one or more previous user intents. 
     In some examples, a secondary user intent of the one or more secondary user intents include a combination of a first previous user intent of the one or more previous user intents and a second previous user intent of the one or more previous user intents. 
     In some examples, determining one or more secondary user intents further comprises generating a plurality of combinations of the primary user intent and the one or more previous user intents. 
     In some examples, determining one or more secondary user intents further comprises determining whether the plurality of combinations includes a combination that cannot be merged. In accordance with a determination that the plurality of combinations includes a user intent combination that cannot be merged, the one or more secondary user intents do not include the combination that cannot be merged. 
     In some examples, the combination that cannot be merged includes more than one value for a parameter that requires a singular value. 
     In some examples, determining one or more secondary user intents further comprises determining whether the one or more previous user intents include an incorrect user intent. In accordance with a determination that the one or more previous user intents include an incorrect user intent. The one or more secondary user intents are not based on the incorrect user intent. 
     In some examples, determining whether the one or more previous user intents include an incorrect user intent comprises determining whether the one or more previous user intents include a third user intent to correct a fourth user intent of the one or more previous user intents. In accordance with a determination that the one or more previous user intents include a third user intent to correct a fourth user intent of the one or more previous user intents, a determination is made that the one or more previous user intents include an incorrect user intent. The fourth user intent is determined to be the incorrect user intent. 
     In some examples, determining whether the one or more previous user intents include an incorrect user intent comprises determining whether the one or more previous user intents include a fifth user intent associated with a user selection of a media item that is inconsistent with the fifth user intent. In accordance with a determination that the one or more previous user intents include a third user intent to correct the incorrect user intent, a determination is made that the one or more previous user intents include an incorrect user intent, where the fifth user intent is determined to be the incorrect user intent. 
     In some examples, processing unit  708  is further configured to determine (e.g., with determining unit  714 ) whether the plurality of combinations includes a combination that is associated with less than a predetermined number of media items. In accordance with a determination that the plurality of combinations includes a combination that is associated with less than a predetermined number of media items, the one or more secondary user intents do not include the combination that is associated with less than a predetermined number of media items. 
     In some examples, processing unit  708  is further configured to determine (e.g., with determining unit  714 ) a ranking score for each of the one or more secondary user intents, where the plurality of secondary sets of media items are displayed in accordance with the ranking score for each of the one or more secondary user intents. 
     In some examples, the ranking score for each of the one or more secondary user intents is determined based on an order in which the media search request and the one or more previous media search requests are received. In some examples, the ranking score for each of the one or more secondary user intents is determined based on a selection history of the user, the selection history comprising media items previously selected by the user. In some examples, the ranking score for each of the one or more secondary user intents is determined based on a media search history of the user. 
     In some example, the primary set of media items are displayed at a top row of a user interface, the plurality of secondary set of media items are displayed in subsequent rows of the user interface, the subsequent rows being below the top row, and each row of the subsequent rows corresponds to a respective secondary user intent of the one or more secondary user intents. 
     In some examples, the subsequent rows are ordered in accordance with the ranking score of each of the one or more secondary user intents. 
     In accordance with some embodiments, processing unit  708  is configured to receive (e.g., at input unit  703  or audio receiving unit  704  and with receiving unit  722  or audio receiving enabling unit  716 ) a first media search request. Processing unit  708  is further configured to obtain (e.g., with obtaining unit  718 ) a first set of media items that satisfies the media search request. Processing unit  708  is further configured to display (e.g., with display enabling unit), on a display unit, the first set of media items via a user interface. While displaying the at least a portion of the first set of media items, processing unit  708  is further configured to receive (e.g., at input unit  703  or audio receiving unit  704  and with receiving unit  722  or audio receiving enabling unit  716 ) a second media search request and obtain (e.g., obtaining unit  718 ) a determination of whether the second media search request is a request to narrow the first media search request. Processing unit  708  is further configured to, in response to obtaining a determination that the second media search request is a request to narrow the first media search request, obtain (e.g., with obtaining unit  718 ) a second set of media items that satisfies the second media search request, the second set of media items being a subset of the plurality of media items, and replace display of at least a portion of the first set of media items on the display unit with display of at least a portion of the second set of media items via the user interface (e.g., with display enabling unit  710 ). 
     In some example, each media item of the second set of media items is associated with one or more parameter values of the first media search request and one or more parameter values of the second media search request. 
     In some examples, processing unit  708  is further configured to display (e.g., with display enabling unit  710 ) media content on the display unit while displaying the first set of media items and while displaying the at least a portion of the second set of media items. 
     In some example, the user interface occupies at least a majority of a display area of the display unit. Processing unit  708  is further configured to obtain (e.g., obtaining unit  718 ) a third set of media items that at least partially satisfies the second media search request, where the second set of media items and the third set of media items are different. Processing unit  708  is further configured to display (e.g., with display enabling unit  710 ), on the display unit, at least a portion of the third set of media items via the user interface. 
     In some examples, each media item of the third set of media items is associated with at least one parameter value defined in the first media search request or the second media search request. In some examples, the at least a portion of the second set of media items is displayed at a top row of the user interface, and wherein the at least a portion of the third set of media items is displayed at one or more subsequent rows on the user interface. 
     In some examples, a focus of the user interface is on a media item of the first set of media items when the second media search request is received, and the third set of media items are contextually-related to the media item of the first set of media items. 
     In some examples, obtaining a determination of whether the second media search request is a request to narrow the media search request comprises obtaining a determination of whether the second media search request contains one of a plurality of refinement terms. 
     In some examples, the second media search request is in natural language form. In some examples, the second media search request defines a parameter value using an ambiguous term. 
     In some examples, processing unit  708  is further configured to identiful (e.g., with identifying unit  720 ), using natural language processing, the parameter value based on a strength of a connection between the ambiguous term and the parameter value. 
     In some examples, each media item of the first set of media items is associated with a quality rating, and the second media search request defines a parameter value associated with the quality rating. In some examples, each media item of the first set of media items is associated with a duration, and wherein the second media search request defines a parameter value associated with the duration. 
     In some examples, each media item of the first set of media items is associated with a popularity rating, and the second media search request defines a parameter value associated with the popularity rating. 
     In some examples, each media item of the first set of media items is associated with a release date, and the second media search request defines a parameter value associated with the release date. 
     In some examples, processing unit  708  is further configured to, in response to obtaining a determination that the second media search request is not a request to narrow the first media search request, obtain (e.g., with obtaining unit  718 ) a fourth set of media items that satisfies the second media search request, the fourth set of media items being different from the first set of media items, and replace display of at least a portion of the first set of media items on the display unit with display of at least a portion of the fourth set of media items via the user interface (e.g., with display enabling unit  710 ). 
     In some examples, each media item of the fourth set of media items is associated with one or more parameters defined in the second media search request. 
     In some examples, processing unit  708  is further configured to display (e.g., with display enabling unit  710 ) media content on the display unit while displaying the first set of media items and while displaying the at least a portion of the fourth set of media items. 
     In some examples, the user interface occupies at least a majority of a display area of the display unit. Processing unit  708  is further configured to obtain (e.g., with obtaining unit  718 ) a fifth set of media items, where each media item of the fifth set of media items is associated with one or more parameters defined in the first media search request and one or more parameters defined in the second media search request. Processing unit  708  is further configured to display (e.g., with display enabling unit  710 ) the fifth set of media items on the display unit via the user interface. 
     In some examples, a focus of the user interface is on a second media item of the first set of media items when the second media search request is received, and one or more media items of the fifth plurality of media items includes a parameter value associated with the second media item of the first set of media items. 
     In some examples, a focus of the user interface is on a third media item of the first set of media items when the second media search request is detected. Processing unit  708  is further configured to, in response to obtaining a determination that the second media search request is not a request to narrow the first media search request, obtain (e.g., with obtaining unit  718 ) a determination of whether the second media search request is a request to obtain an alternative set of media items similar to the third media item of the first set of media items. Processing unit  708  is further configured to, in response to obtaining a determination that the second media search request is a request to obtain an alternative set of media items similar to the third media item of the first set of media items, obtain (e.g., with obtaining unit  718 ) a sixth set of media items, where each media item of the sixth set of media items is associated with one or more parameter values of the third media item, and display (e.g., with display enabling unit  710 ), on the display unit, the sixth set of media items via the user interface. 
     In some examples, the first set of media items is obtained by performing a string search based on the first media search request, and the second set of media items is obtained by performing a structured search based on one or more parameter values defined in the second media search request. 
     In some examples, the first media search request is received via a keyboard interface, and the second media search request is received in natural language speech form. In some examples, the structured search is performed using the first set of media items. 
     The operations described above with reference to  FIGS. 5A-E  are, optionally, implemented by components depicted in  FIGS. 1-3 and 4A -B. For example, displaying operations  502 ,  522 ,  534 ,  540 ,  548 ,  564 ,  568 , detecting operation  504 , determining operations  508 ,  510 ,  538 ,  544 ,  550 ,  552 ,  560 , obtaining operations  520 ,  524 ,  536 ,  546 ,  562 ,  566 , identifying operations  526 ,  528 ,  542 ,  554 , excluding operation  558 , and generating operations  530 ,  556  may be implemented by one or more of operating system  252 , GUI module  256 , applications module  262 , I/O processing module  428 , STT processing module  430 , natural language processing module  432 , task flow processing module  436 , service processing module  438 , or processor(s)  204 ,  404 . It would be clear to a person having ordinary skill in the art how other processes can be implemented based on the components depicted in  FIGS. 1-3 and 4A -B. 
     In accordance with some implementations, a computer-readable storage medium (e.g., a non-transitory computer readable storage medium) is provided, the computer-readable storage medium storing one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for performing any of the methods described herein. 
     In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises means for performing any of the methods described herein. 
     In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises a processing unit configured to perform any of the methods described herein. 
     In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for performing any of the methods described herein. 
     Although the foregoing 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 user input could be termed a second user input, and, similarly, a second user input could be termed a first user input, without departing from the scope of the various described embodiments. 
     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. 
     Further, 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 
     In addition, in any of the various examples discussed herein, various aspects can be personalized for a particular user. User data including contacts, preferences, location, favorite media, and the like can be used to interpret voice commands and facilitate user interaction with the various devices discussed herein. The various processes discussed herein can also be modified in various other ways according to user preferences, contacts, text, usage history, profile data, demographics, or the like. In addition, such preferences and settings can be updated over time based on user interactions (e.g., frequently uttered commands, frequently selected applications, etc.). Gathering and use of user data that is available from various sources can be used to improve the delivery to users of invitational content or any other content that may be of interest to them. The present disclosure contemplates that in some instances, this gathered data can 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 as 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 examples 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 not to 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 examples, the present disclosure also contemplates that the various examples can also be implemented without the need for accessing such personal information data. That is, the various examples 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 publicly available information.