Patent ID: 12254884

Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

In the not too distant future, it is possible that many devices may be continuously listening for hotwords. When a single user has multiple devices trained to respond to their voice (e.g., a phone, tablet, TV, etc.), it may be desirable to suppress responding to hotwords on devices that are not likely to be the ones a user intends to address. For example, when a user speaks the hotword toward one device, if any of their other devices are nearby, it is likely that they will also trigger a voice search. In many cases, this is not the user's intention. Thus, it may be advantageous if only a single device should trigger, specifically the device the user is speaking to. The present specification addresses the problem of selecting the correct device for reacting to a hotword, and suppressing reaction to the hotword on other devices.

FIG.1is a diagram of an example system100for hotword detection. In general, system100illustrates a user102speaking an utterance104that is detected by microphones of computing devices106,108, and110. The computing devices106,108, and110process the utterance104to determine a likelihood that the utterance104includes a hotword. The computing devices106,108, and110each transmit data to each other that indicates the likelihood that the utterance104includes a hotword. The computing devices106,108, and110each compare the data, and the computing device that computed the highest likelihood that the utterance104included a hotword initiates speech recognition on the utterance104. The computing devices that did not compute the highest likelihood that the utterance104includes a hotword do not initiate speech recognition on the speech following the utterance104.

Before transmitting, to another computing device, data that indicates a likelihood that the utterance104corresponds to a hotword, the computing devices that are located near each other identify each other. In some implementations, the computing devices identify each other by searching the local network for other devices that are configured to respond to the hotword. For example, computing device106may search the local area network for other devices that are configured to respond to the hotword and identify computing device108and computing device110.

In some implementations, the computing devices identify other nearby computing devices that are configured to respond to the hotword by identifying the user who is logged into each device. For example, user102is logged into computing devices106,108, and110. The user102has the computing device106is the user's hand. The computing device108is sitting on the table, and the computing device110is located on a nearby wall. Computing device106detects computing devices108and110and each computing device shares information that is related to the user who is logged into the computing device, such as a user identifier. In some implementations, the computing devices may identify other near computing devices that are configured to respond to the hotword by identifying computing devices that are configured to respond when the hotword is spoken by the same user through speaker identification. For example, the user102configured the computing devices106,108, and110each to respond to the voice of user102when user102speaks the hotword. The computing devices share the speaker identification information by providing a user identifier for user102to each other computing device. In some implementations, the computing devices may identify other computing devices that are configured to respond to the hotword through short range radio. For example, the computing device106may transmit a signal through short range radio searching for other computing devices that are configured to respond to the hotword. The computing devices may employ one of these techniques or a combination of them to identify other computing devices that are configured to respond to the hotword.

Once the computing devices106,108, and110have identified other computing devices that are configured to respond to the hotword, the computing devices106,108, and110share and store device identifiers for the identified computing devices. The identifiers may be based on a type of device, an IP address of the device, a MAC address, a name given to the device by a user, or any similar unique identifier. For example, the device identifier112for computing device106may be “phone.” The device identifier114for computing device108may be “tablet.” The device identifier116for computing device110may be “thermostat.” The computing devices106,108, and110store the device identifier for the other computing devices that are configured to respond to the hotword. Each computing device has a device group where the computing device stores the device identifiers. For example, computing device106has device group118that lists “tablet” and “thermostat” as the two devices that will receive the likelihood that the audio data includes the hotword as computed by the computing device106. The computing device108has device group120that lists “phone” and “thermostat” as the two devices that will receive the likelihood that the audio data includes the hotword as computed by the computing device108. The computing device110has device group122that lists “phone” and “tablet” as the two devices that will receive the likelihood that the audio data includes the hotword as computed by the computing device110.

When the user102speaks the utterance104, “OK computer,” each computing device that has a microphone in the vicinity of the user102detects and processes the utterance104. Each computing device detects the utterance104through an audio input device such as a microphone. Each microphone provides audio data to a respective audio subsystem. The respective audio subsystem buffers, filters, and digitizes the audio data. In some implementations, each computing device may also perform endpointing and speaker identification on the audio data. The audio subsystem provides the processed audio data to a hotworder. The hotworder compares the processed audio data to known hotword data and computes a confidence score that indicates the likelihood that the utterance104corresponds to a hotword. The hotworder may extract audio features from the processed audio data such as filterbank energies or mel-frequency cepstral coefficients. The hotworder may use classifying windows to process these audio features such as by using a support vector machine or a neural network. Based on the processing of the audio features, the hotworder124computes a confidence score of 0.85, hotworder126computes a confidence score of 0.6, and hotworder128computes a confidence score of 0.45. In some implementations, the confidence score may be normalized to a scale of zero to one, with a higher number indicating a greater confidence that the utterance104includes a hotword.

Each computing device transmits a respective confidence score data packet to the other computing devices in the device group. Each confidence score data packet includes a respective confidence score and the respective device identifier for the computing device. For example, the computing device106transmits the confidence score data packet130that includes the confidence score of 0.85 and the device identifier “phone” to computing devices in device group118, computing devices108and110. The computing device108transmits the confidence score data packet132that includes the confidence score of 0.6 and the device identifier “tablet” to computing devices in device group120, computing devices106and110. The computing device110transmits the confidence score data packet134that includes the confidence score of 0.45 and the device identifier “thermostat” to computing devices in device group118, computing device106and108.

In some implementations, a computing device may transmit the confidence score data packet if the confidence score satisfies a hotword score threshold. For example, if the hotword score threshold is 0.5, then the computing device110would not transmit the confidence score data packet134to the other computing devices in device group122. The computing devices106and108would still transmit the confidence score data packets130and132to computing devices in device groups118and120, respectively.

In some implementations, the computing device that transmit a confidence score data packet may transmit the confidence score data packet to other computing devices directly. For example, computing device106may transmit the confidence score data packet130to computing devices108and110through a short range radio. The communication protocol used between two computing devices may be universal plug and play. In some implementations, a computing device that transmits a confidence score data packet may broadcast the confidence score data packet. In this instance, the confidence score data packet may be received by the computing devices in the device group and by other computing devices. In some implementations, a computing device that transmits a confidence score data packet may transmit the confidence score data packet to a server and then the server transmits the confidence score data packet to the computing devices in the data group. The server may be located within the local area network of the computing devices or accessible through the Internet. For example, the computing device108sends the confidence score data packet132and the list of computing devices in device group120to a server. The server transmits the confidence score data packet132to computing device106and110. In instances where a computing device that is transmitting the confidence score data packet to another computing device, the receiving computing device may send back a confirmation that the receiving computing device received the confidence score data packet.

Each computing device uses a score comparer to compare the hotword confidence scores that the computing device has received. For example, the computing device106computed a hotword confidence score of 0.85 and received hotword confidence scores of 0.6 and 0.45. In this instance, the score comparer136compares the three scores and identifies the score of 0.85 as the highest. For computing devices108and110, the score comparers138and140reach similar conclusions, identifying the score of 0.85, which corresponds to computing device106, as the highest.

The computing device that determines that its own hotword confidence score is the highest initiates speech recognition on speech data the follows the hotword utterance. For example, the user may speak “OK computer” and computing device106may determine that it has the highest hotword confidence score. The computing device106will initiate speech recognition on audio data received after the hotword. If the user speaks “call Alice,” then the computing device106will process the utterance and execute the appropriate command. In some implementations, receiving a hotword may cause the computing devices that receive the hotword to activate from a sleep state. In this instance, the computing device with the highest hotword confidence score remains in an awake state while the other computing devices that do not have the highest hotword confidence score do not process speech data that follows the hotword utterance and enter a sleep state.

As illustrated inFIG.1, the score comparer136identified the hotword confidence score corresponding to computing device106to be the highest. Therefore, the device status142is “awake.” The score comparers138and140also identified the hotword confidence score corresponding to computing device106to be the highest. Therefore, the device statuses138and140are “asleep.” In some implementations, the activation state of the computing device may be unaffected. For example, the user102may be watching a movie on the computing device108and have the computing device106in the user's hand. When the user102speaks “OK computer,” the computing device106, by virtue of having the highest hotword confidence score, initiates speech recognition on the audio data following the hotword. The computing device108does not initiate speech recognition on the audio data following the hotword, and continues to play the movie.

In some implementations, the computing device that determines that it has the highest hotword confidence score waits for a particular amount of time before beginning to perform speech recognition on speech following the hotword. Doing so allows a computing device that computed the highest hotword confidence score to begin performing speech recognition on speech that follows the hotword without waiting for a higher hotword confidence score. To illustrate, the score comparer136of computing device106received hotword confidence scores of 0.6 and 0.45 from computing device108and110, respectively, as well as the hotword confidence score of 0.85 from the hotworder124. From the time that the hotworder124computes a hotword confidence score of the “Ok computer” audio data, the computing device106waits five hundred milliseconds before performing speech recognition on speech that follows the hotword. In instances where the score comparer receives a higher score, the computing device may not wait for a particular amount of time before setting the device status to “sleep.” For example, the hotworder126of computing device108computes a hotword confidence score of 0.6 and receives hotword confidence scores of 0.85 and 0.45. Once the computing device108receives the hotword confidence score of 0.85, then the computing device108can set the device status144to “sleep.” This assumes that the computing device108receives the hotword confidence score of 0.85 within the particular amount of time after the hotworder126computes the hotword confidence score of 0.6.

In some implementations, when a computing device has the highest hotword confidence score, the computing device may continue to broadcast the confidence score data packet for a particular amount of time to ensure that other computing devices receive the confidence score data packet. This strategy would be most applicable in instances where a computing device does send back a confirmation once it receives a confidence score data packet from another computing device. Therefore, if the computing device106transmits the confidence score data packet130to computing devices in data group118and receives a confirmation before a particular amount of time such as five hundred milliseconds, then the computing device106may begin to perform speech recognition on speech following the hotword. In instances where computing devices broadcast their confidence score data packets and do not expect confirmation, the computing device may continue to broadcast their hotword confidence scores for a particular amount of time, such as five hundred milliseconds, or until the computing device receives a higher hotword confidence score, whichever comes first. For example, computing device110computes a hotword confidence score of 0.45 and begins to broadcast the confidence score data packet134. After three hundred milliseconds, the computing device110receives confidence score data packet130and stops broadcasting the confidence score data packet134because the hotword confidence score of 0.85 from confidence score data packet130is higher than the hotword confidence score of forty five. As another broadcast example, computing device106computes a hotword confidence score of 0.45 and begins to broadcast the confidence score data packet130. After five hundred milliseconds, the computing device106stops broadcasting confidence score data packet130and begins to perform speech recognition on speech following the hotword. The computing device106may receive the confidence score data packets132and134before five hundred milliseconds has elapsed, but because the hotword confidence scores in the confidence score data packets132and134are lower than 0.85, the computing device continues to wait until after the five hundred milliseconds has elapsed.

In some implementations, the computing device may begin to perform speech recognition on speech following the hotword until the computing device receives a higher hotword confidence score. The hotworder computes a hotword confidence score and if the hotword confidence score satisfies a threshold, then the computing device performs speech recognition on speech following the hotword. The computing device may perform the speech recognition without displaying any indication of the speech recognition to the user. This may be desirable because doing so gives the user the impression that the computing device is not active while also allowing the computing device to display results based on the speech recognition to the user quicker than if the computing device had waited until the computing device confirmed that it computed the highest hotword score. As an example, the computing device106computes a hotword confidence score of 0.85 and begins to perform speech recognition on speech following the hotword. The computing device106receives confidence score data packets132and134and determines that the hotword confidence score of 0.85 is the highest. The computing device106continues to perform speech recognition on speech following the hotword and presents the results to the user. For computing device108, the hotworder126computes a hotword confidence score of 0.6 and the computing device108begins to perform speech recognition on speech following the hotword without displaying data to the user. Once the computing device108receives the confidence score data packet130that includes the hotword confidence of 0.85, the computing device stops performing speech recognition. No data is displayed to the user, and the user is likely under the impression that the computing device108has remained in a “sleep” state.

In some implementations, to avoid any latency after a hotword is spoken, scores could be reported from the hotworder before the end of the hotword, e.g. for a partial hotword. For example, as a user is speaking “Ok computer,” a computing device could compute a partial hotword confidence score once the user has finished speaking “OK comp.” The computing device can then share the partial hotword confidence score with other computing devices. The computing device with the highest partial hotword confidence score can continue to process the user's speech.

In some implementations, a computing device may emit an audible or inaudible sound, e.g., of a particular frequency or frequency pattern, when the computing device determines that a hotword confidence score satisfies a threshold. The sound would signal to other computing devices that the computing device will continue to process the audio data following the hotword. Other computing devices would receive this sound and cease processing of the audio data. For example, a user speaks “Ok computer.” One of the computing devices computes a hotword confidence score that is greater than or equal to a threshold. Once the computing device determines that the hotword confidence score is greater than or equal two a threshold, the computing device emits a sound of eighteen kilohertz. The other computing devices in the vicinity of the user may also be computing a hotword confidence score and may be in the middle of computing a hotword confidence score when the other computing devices receive the sound. When the other computing devices receive the sound, the other computing devices cease processing of the user's speech. In some implementations, the computing device may encode the hotword confidence score in the audible or inaudible sound. For example, if the hotword confidence score is 0.5, then the computing device may generate an audible or inaudible sound that includes a frequency pattern that encodes the score of 0.5.

In some implementations, the computing devices may use different audio metrics to select a computing device to continue processing the user's speech. For example, the computing devices may use loudness to determine which computing device will continue to process the user's speech. The computing device that detects the loudest speech may continue to process the user's speech. As another example, the computing device that is currently in use or has an active display may notify the other computing devices that it will continue to processes the user's speech upon detecting a hotword.

In some implementations, each computing device that is in the vicinity of the user while the user is speaking receives the audio data and sends the audio data to a server to improve speech recognition. Each computing device can receive the audio data that corresponds to the user's speech. While only one computing device will appear to the user to be processing the user's speech, each computing device can transmit the audio data to a server. The server can then use the audio data that is received from each computing device to improve speech recognition because the server can compare different audio samples that correspond to the same utterance. For example, a user says “Ok computer, remind me to buy milk.” Once the user finishes speaking “Ok computer,” the nearby computing devices will have likely determined which computing device has the highest hotword confidence score and that computing device will process and respond “remind me to buy milk” as the user speaks those words. The other computing devices will also receive “remind me to buy milk.” While the other computing device will not respond to the “remind me to buy milk” utterance, the other computing devices can send audio data corresponding to “remind me to buy milk” to a server. The computing devices responding to “remind me to buy milk” can also send its audio data to the server. The server can process the audio data to improve speech recognition because the server has different audio samples from different computing devices that correspond to the same “remind me to buy milk” utterance.

FIG.2is a diagram of an example process200for hotword detection. The process200may be performed by a computing device such as the computing device108fromFIG.1. The process200computes a value that corresponds a likelihood that an utterance includes a hotword and compares the value to other values computed by other computing devices to determine whether or not to perform speech recognition on the portion of the utterance after the hotword.

The computing device receives audio data that corresponds to an utterance (210). A user speaks the utterance and a microphone of the computing device receives the audio data of the utterance. The computing device processes the audio data by buffering, filtering, endpointing, and digitizing the audio data. As an example, the user may utter “Ok, computer” and the microphone of the computing device will receive the audio data that corresponds to “Ok, computer.” An audio subsystem of the computing device will sample, buffer, filter, and endpoint the audio data for further processing by the computing device.

The computing device determines a first value corresponding to a likelihood that the utterance includes a hotword (220). The computing device determines the first value, which may be referred to as a hotword confidence score, by comparing the audio data of the utterance to a group of audio samples that include the hotword or by analyzing the audio characteristics of the audio data of the utterance. The first value may be normalized to a scale from zero to one where one indicates the highest likelihood that the utterance includes a hotword. In some implementations, the computing device identifies a second computing device and determines that the second computing device is configured to respond to utterances that include the hotword and is configured by the user to be responsive to the hotword. The user may be logged into both the computing device and the second computing device. Both the computing device and the second computing device may be configured to respond to the user's voice. The computing device and the second computing device may be connected to the same local area network. The computing device and the second computing device may both be located within a particular distance of each other, such as ten meters, as determined by GPS or signal strength. For example, the computing devices may communicate by a short range radio. The computing device may detect a strength of a signal being transmitted by the second computing device as five dBm and translate that a corresponding distance such as five meters.

The computing device receives a second value corresponding to a likelihood that the utterance includes the hotword, the second value being determined by a second computing device (230). The second computing device receives the utterance through a microphone of the second computing device. The second computing device processes the received audio data that corresponds to the utterance and determines a second value or a second hotword confidence score. The second hotword confidence score reflect the likelihood, as calculated by the second computing device, that the utterance includes a hotword. In some implementations, the computing device transmits the first value to the second computing device using one or more of the following techniques. The computing device may transmit the first value to the second computing device through a server accessible through the Internet, through a server that is located on the local area network, or directly through the local area network or a short range radio. The computing device may transmit the first value only to the second computing device or the computing device may broadcast the first value so that other computing devices may also receive the first value. The computing device may receive the second value from the second computing device using the same or different technique as the computing device transmitted the first value.

In some implementations, the computing device may compute a loudness score for the utterance or a signal to noise ratio for the utterance. The computing device may combine the loudness score, the signal to noise ratio, and the hotword confidence score to determine a new value for comparing to similar values from other computing devices. For example, the computing device may compute a hotword confidence score and a signal to noise ratio. The computing device may then combine those two scores and compare to similarly computed scores from other computing devices. In some implementations, the computing device may compute different scores and transmit each score to other computing devices for comparison. For example, the computing device may compute a loudness score for the utterance and a hotword confidence score. The computing device may then transmit those scores to other computing devices for comparison.

In some implementations, the computing device may transmit a first identifier with the first value. The identifier may be based on one or more of an address of the computing device, a name of the computing device given by the user, or a location of the computing device. For example, an identifier may be “69.123.132.43” or “phone.” Similarly, the second computing device may transmit a second identifier with the second value. In some implementations, the computing device may transmit the first identifier to particular computing devices that the computing device previously identified as configured to respond to the hotword. For example, the computing device may have previously identified the second computing device as configured to respond to the hotword because, in addition to being able to respond to a hotword, the same user was logged into the second computing device as the computing device.

The computing device compares the first value and the second value (240). The computing device then initiates, based on the result of the comparison, speech recognition processing on the audio data (250). In some implementations, for example, the computing device initiates speech recognition when the first value is greater than or equal to the second value. If the user spoke “ok computer, call Carol,” then the computing device would begin to process “call Carol” by performing speech recognition on “call Carol” because the first value is greater than or equal to second value. In some implementations, the computing device sets an activation state. In instances where the first value is greater than or equal to the second value, then the computing device sets the activation state as active or “awake.” In the “awake” state, the computing device displays results from the speech recognition.

In some implementations, the computing device compares the first value and the second value and determines that the first value is less than the second value. The computing device, based on determining that the first value is less than the second value, sets the activation state as inactive or “sleep.” In the “sleep” state, the computing device does not appear, to the user, to be active or processing the audio data.

In some implementations, when the computing device determines that the first value is greater than or equal to the second value, the computing device may wait for a particular amount of time before setting the activation state to active. The computing device may wait for the particular amount of time to increase the probability that the computing device will not receive a higher value from another computing device. The particular amount of time may be fixed or may vary depending on the technique that the computing devices transmit and receive values. In some implementations, when the computing device determines that the first value is greater than or equal to the second value, the computing device may continue to transmit the first value for a particular amount of time. By continuing to transmit the first value for a particular amount of time, the computing device increases the probability that the first value is received by the other computing devices. In instances where the computing device determines that the first value is less than the second value, the computing device may stop transmitting the first value.

In some implementations, the computing device may consider additional information in determining whether to execute the command following the hotword. One example of the additional information may be the portion of the utterance that follows the hotword. Typically, the audio data that follows the hotword corresponds to a command for the computing device such as “call Sally,” “play Halloween Movie,” or “set heat to 70 degrees.” The computing device may identify a typical device that handles the type of request or that is capable of handling the request. A request to call a person would be typically handled by a phone based on pre-programed typical usages or based on usage patterns of a user of the device. If the user typically watches movies on a tablet, then the tablet may handle a request to play a movie. If the thermostat is capable of adjusting the temperature, then the thermostat may handle temperature adjustments.

For the computing device to consider the portion of the utterance that follows the hotword, the computing device would have to initiate speech recognition on the audio data once it likely identifies a hotword. The computing device may categorize the command portion of the utterance and compute a frequency of commands in that category. The computing device may transmit the frequency along with the hotword confidence score to other computing devices. Each computing device may use the frequencies and the hotword confidence scores to determine whether to execute the command following the hotword.

For example, if the user utters “OK computer, play Michael Jackson,” then if the computing device is a phone that the user use's twenty percent of the time to listen to music, then the computing device may transmit that information along with the hotword confidence score. A computing device such as a tablet that the user uses five percent of the time to listen to music may transmit that information along with the hotword confidence score to other computing devices. The computing devices may use a combination of the hotword confidence score and the percentage of time playing music to determine whether to execute the command.

FIG.3shows an example of a computing device300and a mobile computing device350that can be used to implement the techniques described here. The computing device300is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The mobile computing device350is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart-phones, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.

The computing device300includes a processor302, a memory304, a storage device306, a high-speed interface308connecting to the memory304and multiple high-speed expansion ports310, and a low-speed interface312connecting to a low-speed expansion port314and the storage device306. Each of the processor302, the memory304, the storage device306, the high-speed interface308, the high-speed expansion ports310, and the low-speed interface312, are interconnected using various busses, and may be mounted on a common motherboard or in other manners as appropriate. The processor302can process instructions for execution within the computing device300, including instructions stored in the memory304or on the storage device306to display graphical information for a GUI on an external input/output device, such as a display316coupled to the high-speed interface308. In other implementations, multiple processors and/or multiple buses may be used, as appropriate, along with multiple memories and types of memory. Also, multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).

The memory304stores information within the computing device300. In some implementations, the memory304is a volatile memory unit or units. In some implementations, the memory304is a non-volatile memory unit or units. The memory304may also be another form of computer-readable medium, such as a magnetic or optical disk.

The storage device306is capable of providing mass storage for the computing device300. In some implementations, the storage device306may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. Instructions can be stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor302), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices such as computer- or machine-readable mediums (for example, the memory304, the storage device306, or memory on the processor302).

The high-speed interface308manages bandwidth-intensive operations for the computing device300, while the low-speed interface312manages lower bandwidth-intensive operations. Such allocation of functions is an example only. In some implementations, the high-speed interface308is coupled to the memory304, the display316(e.g., through a graphics processor or accelerator), and to the high-speed expansion ports310, which may accept various expansion cards (not shown). In the implementation, the low-speed interface312is coupled to the storage device306and the low-speed expansion port314. The low-speed expansion port314, which may include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet) may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

The computing device300may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server320, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer322. It may also be implemented as part of a rack server system324. Alternatively, components from the computing device300may be combined with other components in a mobile device (not shown), such as a mobile computing device350. Each of such devices may contain one or more of the computing device300and the mobile computing device350, and an entire system may be made up of multiple computing devices communicating with each other.

The mobile computing device350includes a processor352, a memory364, an input/output device such as a display354, a communication interface366, and a transceiver368, among other components. The mobile computing device350may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage. Each of the processor352, the memory364, the display354, the communication interface366, and the transceiver368, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.

The processor352can execute instructions within the mobile computing device350, including instructions stored in the memory364. The processor352may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor352may provide, for example, for coordination of the other components of the mobile computing device350, such as control of user interfaces, applications run by the mobile computing device350, and wireless communication by the mobile computing device350.

The processor352may communicate with a user through a control interface358and a display interface356coupled to the display354. The display354may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interface356may comprise appropriate circuitry for driving the display354to present graphical and other information to a user. The control interface358may receive commands from a user and convert them for submission to the processor352. In addition, an external interface362may provide communication with the processor352, so as to enable near area communication of the mobile computing device350with other devices. The external interface362may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

The memory364stores information within the mobile computing device350. The memory364can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. An expansion memory374may also be provided and connected to the mobile computing device350through an expansion interface372, which may include, for example, a SIMM (Single In Line Memory Module) card interface. The expansion memory374may provide extra storage space for the mobile computing device350, or may also store applications or other information for the mobile computing device350. Specifically, the expansion memory374may include instructions to carry out or supplement the processes described above, and may include secure information also. Thus, for example, the expansion memory374may be provide as a security module for the mobile computing device350, and may be programmed with instructions that permit secure use of the mobile computing device350. In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner.

The memory may include, for example, flash memory and/or NVRAM memory (non-volatile random access memory), as discussed below. In some implementations, instructions are stored in an information carrier. that the instructions, when executed by one or more processing devices (for example, processor352), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory364, the expansion memory374, or memory on the processor352). In some implementations, the instructions can be received in a propagated signal, for example, over the transceiver368or the external interface362.

The mobile computing device350may communicate wirelessly through the communication interface366, which may include digital signal processing circuitry where necessary. The communication interface366may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others. Such communication may occur, for example, through the transceiver368using a radio-frequency. In addition, short-range communication may occur, such as using a Bluetooth, WiFi, or other such transceiver (not shown). In addition, a GPS (Global Positioning System) receiver module370may provide additional navigation- and location-related wireless data to the mobile computing device350, which may be used as appropriate by applications running on the mobile computing device350.

The mobile computing device350may also communicate audibly using an audio codec360, which may receive spoken information from a user and convert it to usable digital information. The audio codec360may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device350. Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by applications operating on the mobile computing device350.

The mobile computing device350may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone380. It may also be implemented as part of a smart-phone382, personal digital assistant, or other similar mobile device.

Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

Although a few implementations have been described in detail above, other modifications are possible. For example, while a client application is described as accessing the delegate(s), in other implementations the delegate(s) may be employed by other applications implemented by one or more processors, such as an application executing on one or more servers. In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. In addition, other actions may be provided, or actions may be eliminated, from the described flows, and other components may be added to, or removed from, the described systems. Accordingly, other implementations are within the scope of the following claims.