Abstract: Techniques for performing command processing are described. A system receives, from a device, input data corresponding to a command. The system determines NLU processing results associated with multiple applications. The system also determines NLU confidences for the NLU processing results for each application. The system sends NLU processing results to a portion of the multiple applications, and receives output data or instructions from the portion of the applications. The system ranks the portion of the applications based at least in part on the NLU processing results associated with the portion of the applications as well as the output data or instructions provided by the portion of the applications. The system may also rank the portion of the applications using other data. The system causes content corresponding to output data or instructions provided by the highest ranked application to be output to a user.

Abstract: A speech recognition platform configured to receive an audio signal that includes speech from a user and perform automatic speech recognition (ASR) on the audio signal to identify ASR results. The platform may identify: (i) a domain of a voice command within the speech based on the ASR results and based on context information associated with the speech or the user, and (ii) an intent of the voice command. In response to identifying the intent, the platform may perform a corresponding action, such as streaming audio to the device, setting a reminder for the user, purchasing an item on behalf of the user, making a reservation for the user or launching an application for the user. The speech recognition platform, in combination with the device, may therefore facilitate efficient interactions between the user and a voice-controlled device.

Abstract: Techniques for limiting natural language processing performed on input data are described. A system receives input data from a device. The input data corresponds to a command to be executed by the system. The system determines applications likely configured to execute the command. The system performs named entity recognition and intent classification with respect to only the applications likely configured to execute the command.

Abstract: Techniques for synchronously outputting content by one or more devices are described. A system may receive a user command and may receive content responsive to the command from an application(s). The content may include various kinds of data (e.g., audio data, image data, video data, etc.). The system may also receive a presentation framework from the application, with the presentation framework indicating how content responsive to the input command should be synchronously output by one or more devices. The system determines one or more devices proximate to the user, determines which of the one or more devices may be used to output content indicated in the presentation framework, and causes the one or more devices to output content in a synchronous manner.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Abstract: A voice-controlled device may receive a voice command uttered by a user, where the voice command may request that the voice-controlled device perform an operation. The voice-controlled device and/or one or more remote computing resources may process an audio signal associated with the voice command to determine text corresponding to the voice command. The resulting user utterance may be associated with a unique identifier, which may be provided to a third party and/or third party application that is to provide information responsive to the user request. The information provided by the third party/third party application may be output to the user based at least partly on the unique identifier, without disclosing user data associated with the user.

Abstract: Systems and methods for audio output control are disclosed. Audio may be output via a speaker of a communal device associated with a first portion of an environment. A user may provide a user utterance indicating an intent to add another device in a second portion of the environment to the audio-output session, and/or an intent to move the audio-output session from the first device to the second device, and/or an intent to remove a device from an audio-output session. Based on this determined intent, audio-session queues may be associated and dissociated from devices and device states may be altered to effectuate the intent of the user utterance.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Abstract: A language-based system may be configured to interact with a user by understanding natural language of the user and may provide functions and services in response to such natural language. Certain functions and services may be provided by third-party applications that register serviceable intents with the language-based system. A serviceable intent indicates an intent that the third-party application is able to fulfill or service. Upon determining an intent of the user based on natural language interaction with the user, the system identifies one of the third-party applications that has specified a matching serviceable intent and selects that application for use by the user.

Abstract: A speech-based system includes a local device in a user premises and a network-based control service that directs the local device to perform actions for a user. The control service may specify a first action that is to be performed upon detection by the local device of a stimulus. In some cases, performing the first action may rely on the availability of network communications with the control service or with another service. In these cases, the control service also specifies a second, fallback action that does not rely upon network communications. Upon detecting the stimulus, the local device performs the first action if network communications are available. If network communications are not available, the local device performs the second, fallback action.

Abstract: Techniques for creating a persistent connection between client devices and one or more remote computing resources, which may form a portion of a network-accessible computing platform. This connection may be considered “permanent” or “nearly permanent” to allow the client device to both send data to and receive data from the remote resources at nearly any time. In addition, both the client device and the remote resources may establish virtual channels over this single connection. If no data is exchanged between the client device and the remote computing resources for a threshold amount of time, then the connection may be severed and the client device may attempt to establish a new connection with the remote computing resources.

Abstract: Systems and methods for audio output control are disclosed. Audio may be output via a speaker of a communal device associated with a first portion of an environment. A user may provide a user utterance indicating an intent to add another device in a second portion of the environment to the audio-output session, and/or an intent to move the audio-output session from the first device to the second device, and/or an intent to remove a device from an audio-output session. Based on this determined intent, audio-session queues may be associated and dissociated from devices and device states may be altered to effectuate the intent of the user utterance.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Abstract: A speech-based system includes a local device in a user premises and a remote service that uses the local device to conduct speech dialogs with a user. The local device may also be directed to play audio such as music, audio books, etc. When designating audio for playing by the local device, the remote service may specify that the audio is either background audio or foreground audio. For background audio, the service indicates whether the background audio is mixable. For foreground audio, the service indicates an interrupt behavior. When the local device is playing background audio and receives foreground audio, the background audio is paused, attenuated, or not changed based on the indicated interrupt behavior of the foreground audio and whether the background audio has been designated as being mixable.

Abstract: A speech recognition platform configured to receive an audio signal that includes speech from a user and perform automatic speech recognition (ASR) on the audio signal to identify ASR results. The platform may identify: (i) a domain of a voice command within the speech based on the ASR results and based on context information associated with the speech or the user, and (ii) an intent of the voice command. In response to identifying the intent, the platform may perform a corresponding action, such as streaming audio to the device, setting a reminder for the user, purchasing an item on behalf of the user, making a reservation for the user or launching an application for the user. In some instances, the speech recognition platform engages in a back-and-forth dialog with the user in order to properly fulfill the user's request.

Abstract: Features are disclosed for presenting multiple media items based on one or more rules defining how the items are to be presented. One media item may be presented, and during presentation any number of additional media items may be received or scheduled for presentation. Rules may define which media items have priority over others, which media items may interrupt others or be interrupted, which media items may be delayed or presented early, whether particular media items are time-critical such that they are not to be delayed but rather should take presentation priority over others, etc. Metadata may be associated with particular media items or categories thereof. The metadata can provide details regarding how the rules should be applied to those media items. User feedback may also be obtained, and may affect the further application of the rules.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Abstract: Techniques for creating a persistent connection between client devices and one or more remote computing resources, which may form a portion of a network-accessible computing platform. This connection may be considered “permanent” or “nearly permanent” to allow the client device to both send data to and receive data from the remote resources at nearly any time. In addition, both the client device and the remote resources may establish virtual channels over this single connection. If no data is exchanged between the client device and the remote computing resources for a threshold amount of time, then the connection may be severed and the client device may attempt to establish a new connection with the remote computing resources.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.