Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Stephen Frederick Potter

Rohit Prasad

Nikko Strom

Hsiao-Wuen Hon

Francisco Manuel Galanes

Renaud Julien Lecoeuche

James D Jacoby

Ruhi Sarikaya

Spyridon Matsoukas

William Folwell Barton

Young-Bum Kim

Frédéric Johan Georges Deramat

Kerry Hammil

Ariya Rastrow

Yuzo Watanabe

Susan M Warren

Madan Mohan Rao Jampani

Arushan Rajasekaram

Renaud J Lecoueche

Steven Young

Gregory Michael Hart

Tal Saraf

Julian James Odell

Scott Ian Blanksteen

Lambert Leo Mathias

David Gareth Ollason

Caroline Elizabeth Matheson

Anthony W Bowker

Steve Sung-Nam Chang

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.

Natural language speech processing application selection

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.

Generation of predictive natural language processing models

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.

System command processing

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.

Selecting from multiple content sources

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.

Identification using audio signatures and additional characteristics

Fuel burner container

Fuel burner stand

Web server controls are provided for generating client side markups with recognition and/or audible prompting. Three approaches are disclosed for implementation of the controls.

Web server controls for web enabled recognition and/or audible prompting

Controls are provided for a web server to generate client side markups that include recognition and/or audible prompting. The controls comprise elements of a dialog such as a question, answer, confirmation, command or statement. A module forms a dialog by making use of the information carried in the controls.

Application abstraction with dialog purpose

A method of analyzing dialog between a user and an interactive application having dialog turns is provided. The method includes accessing information indicative of a plurality of dialog turns between the application and at least one user and identifying instances where the application determined a response was received before an associated prompt had completed. The accessed information includes information related to operation of the application with a first grammar to recognize the response. The method includes identifying whether the response was received in a particular limited time period from when the associated prompt began. If the response was received in the limited time period, the method determines whether the response included one or more terms from the associated prompt by performing recognition on the response using a second grammar having more information related to grammar of a language than the first grammar.

Automatic identification of dialog timing problems for an interactive speech dialog application using speech log data indicative of cases of barge-in and timing problems

A computer implemented method of analyzing recognition results between a user in an interactive application having dialogue turns includes receiving and storing information on a computer indicative of dialogue turns between the system and at least one user. The method also utilizes a computer recognition analysis module comprising an inference module operable on a computer to associate an inferred value of a response with a turn where the inferred value is based on analyzing the received information without performing transcription of the user response within the inference module. The method also includes outputting the inferred value.

Computer implemented method of analyzing recognition results between a user and an interactive application utilizing inferred values instead of transcribed speech

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Seattle, WA, United States of America

Stephen Frederick Potter