Patents by Inventor Kevin Kilgour
Kevin Kilgour has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20230143177Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.Type: ApplicationFiled: January 3, 2023Publication date: May 11, 2023Inventors: Victor Carbune, Matthew Sharifi, Ondrej Skopek, Justin Lu, Daniel Valcarce, Kevin Kilgour, Mohamad Hassan Rom, Nicolo D'Ercole, Michael Golikov
-
Patent number: 11557293Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.Type: GrantFiled: May 17, 2021Date of Patent: January 17, 2023Assignee: GOOGLE LLCInventors: Victor Carbune, Matthew Sharifi, Ondrej Skopek, Justin Lu, Daniel Valcarce, Kevin Kilgour, Mohamad Hassan Rom, Nicolo D'Ercole, Michael Golikov
-
Publication number: 20220366903Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.Type: ApplicationFiled: May 17, 2021Publication date: November 17, 2022Inventors: Victor Carbune, Matthew Sharifi, Ondrej Skopek, Justin Lu, Daniel Valcarce, Kevin Kilgour, Mohamad Hassan Rom, Nicolo D'Ercole, Michael Golikov
-
Publication number: 20220262345Abstract: A method of training a custom hotword model includes receiving a first set of training audio samples. The method also includes generating, using a speech embedding model configured to receive the first set of training audio samples as input, a corresponding hotword embedding representative of a custom hotword for each training audio sample of the first set of training audio samples. The speech embedding model is pre-trained on a different set of training audio samples with a greater number of training audio samples than the first set of training audio samples The method further includes training the custom hotword model to detect a presence of the custom hotword in audio data. The custom hotword model is configured to receive, as input, each corresponding hotword embedding and to classify, as output, each corresponding hotword embedding as corresponding to the custom hotword.Type: ApplicationFiled: May 4, 2022Publication date: August 18, 2022Applicant: Google LLCInventors: Matthew Sharifi, Kevin Kilgour, Dominik Roblek, James Lin
-
Patent number: 11341954Abstract: A method of training a custom hotword model includes receiving a first set of training audio samples. The method also includes generating, using a speech embedding model configured to receive the first set of training audio samples as input, a corresponding hotword embedding representative of a custom hotword for each training audio sample of the first set of training audio samples. The speech embedding model is pre-trained on a different set of training audio samples with a greater number of training audio samples than the first set of training audio samples. The method further includes training the custom hotword model to detect a presence of the custom hotword in audio data. The custom hotword model is configured to receive, as input, each corresponding hotword embedding and to classify, as output, each corresponding hotword embedding as corresponding to the custom hotword.Type: GrantFiled: December 17, 2019Date of Patent: May 24, 2022Assignee: Google LLCInventors: Matthew Sharifi, Kevin Kilgour, Dominik Roblek, James Lin
-
Publication number: 20210183367Abstract: A method of training a custom hotword model includes receiving a first set of training audio samples. The method also includes generating, using a speech embedding model configured to receive the first set of training audio samples as input, a corresponding hotword embedding representative of a custom hotword for each training audio sample of the first set of training audio samples. The speech embedding model is pre-trained on a different set of training audio samples with a greater number of training audio samples than the first set of training audio samples. The method further includes training the custom hotword model to detect a presence of the custom hotword in audio data. The custom hotword model is configured to receive, as input, each corresponding hotword embedding and to classify, as output, each corresponding hotword embedding as corresponding to the custom hotword.Type: ApplicationFiled: December 17, 2019Publication date: June 17, 2021Applicant: Google LLCInventors: Matthew Sharifi, Kevin Kilgour, Dominik Roblek, James Lin
-
Publication number: 20190102458Abstract: In general, the subject matter described in this disclosure can be embodied in methods, systems, and program products. A computing device stores reference song characterization data and receives digital audio data. The computing device determines whether the digital audio data represents music and then performs a different process to recognize that the digital audio data represents a particular reference song. The computing device then outputs an indication of the particular reference song.Type: ApplicationFiled: October 1, 2018Publication date: April 4, 2019Inventors: Dominik Roblek, Blaise Aguera-Arcas, Tom Hume, Marvin Ritter, Brandon Barbello, Kevin Kilgour, Mihajlo Velimirovic, Christopher Walter George Thornton, Gabriel Taubman, James David Lyon, Jan Athaus, Katsiaryna Naliuka, Julian Odell, Matthew Sharifi, Beat Gfeller
-
Publication number: 20190102144Abstract: In general, the subject matter described in this disclosure can be embodied in methods, systems, and program products for indicating a reference song. A computing device stores reference song characterization data that identifies a plurality of audio characteristics for each reference song in a plurality of reference songs. The computing device receives digital audio data that represents audio recorded by a microphone, converts the digital audio data from time-domain format into frequency-domain format, and uses the digital audio data in the frequency-domain format in a music-characterization process. In response to determining that characterization values for the digital audio data are most relevant to characterization values for a particular reference song, the computing device outputs an indication of the particular reference song.Type: ApplicationFiled: October 1, 2018Publication date: April 4, 2019Inventors: Dominik Roblek, Blaise Aguera-Arcas, Tom Hume, Marvin Ritter, Brandon Barbello, Kevin Kilgour, Mihajlo Velimirovic, Christopher Walter George Thornton, Gabriel Taubman, James David Lyon, Jan Althaus, Katsiaryna Naliuka, Julian Odell, Matthew Sharifi, Beat Gfeller