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: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.

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 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: 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: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.

Abstract: Features are disclosed for generating predictive personal natural language processing models based on user-specific profile information. The predictive personal models can provide broader coverage of the various terms, named entities, and/or intents of an utterance by the user than a personal model, while providing better accuracy than a general model. Profile information may be obtained from various data sources. Predictions regarding the content or subject of future user utterances may be made from the profile information. Predictive personal models may be generated based on the predictions. Future user utterances may be processed using the predictive personal models.

Abstract: A speech-based system may be configured to receive and act upon spoken requests from a user. In some cases, a spoken request may ask the system to play content such as music without specifying from which of multiple available content sources the music is to be obtained. In response to such a request, the system analyzes feature scores for each of the content sources. The feature scores indicate usage characteristics of the different sources by a current user or groups of users. The features scores for a particular source may be averaged or otherwise combined to create a composite score, and the source having the highest composite score is selected as the source of the requested content.

Abstract: Techniques for using both speaker-identification information and other characteristics associated with received voice commands to determine how and whether to respond to the received voice commands. A user may interact with a device through speech by providing voice commands. After beginning an interaction with the user, the device may detect subsequent speech, which may originate from the user, from another user, or from another source. The device may then use speaker-identification information and other characteristics associated with the speech to attempt to determine whether or not the user interacting with the device uttered the speech. The device may then interpret the speech as a valid voice command and may perform a corresponding operation in response to determining that the user did indeed utter the speech. If the device determines that the user did not utter the speech, however, then the device may refrain from taking action on the speech.

Abstract: Monitoring a spoken-word audio stream for a relevant concept is disclosed. A speech recognition engine may recognize a plurality of words from the audio stream. Function words that do not indicate content may be removed from the plurality of words. A concept may be determined from at least one word recognized from the audio stream. The concept may be determined via a morphological normalization of the plurality of words. The concept may be associated with a time related to when the at least one word was spoken. A relevance metric may be computed for the concept. Computing the relevance metric may include assessing the temporal frequency of the concept within the audio stream. The relevance metric for the concept may be based on respective confidence scores of the at least one word. The concept, time, and relevance metric may be displayed in a graphical display.

Abstract: Monitoring a spoken-word audio stream for a relevant concept is disclosed. A speech recognition engine may recognize a plurality of words from the audio stream. Function words that do not indicate content may be removed from the plurality of words. A concept may be determined from at least one word recognized from the audio stream. The concept may be determined via a morphological normalization of the plurality of words. The concept may be associated with a time related to when the at least one word was spoken. A relevance metric may be computed for the concept. Computing the relevance metric may include assessing the temporal frequency of the concept within the audio stream. The relevance metric for the concept may be based on respective confidence scores of the at least one word. The concept, time, and relevance metric may be displayed in a graphical display.

Abstract: An arc detector comprising a voltage generator for detecting a voltage and an integrator for integrating said voltage with respect to time and generating an output signal corresponding to said integration. The arc detector also includes a discharge controller for controlling said output signal of said integrator, an amplifier for amplifying said output signal from said integrator and outputting an amplified signal; and a comparator for comparing said amplified output signal to a reference voltage and generating a detection signal based on said comparison.

Abstract: An arc detector comprising a voltage generator for detecting a voltage and an integrator for integrating said voltage with respect to time and generating an output signal corresponding to said integration. The arc detector also includes a discharge controller for controlling said output signal of said integrator, an amplifier for amplifying said output signal from said integrator and outputting an amplified signal; and a comparator for comparing said amplified output signal to a reference voltage and generating a detection signal based on said comparison.