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公开(公告)号:US20200219517A1
公开(公告)日:2020-07-09
申请号:US16242541
申请日:2019-01-08
Applicant: Google LLC
Inventor: Chong Wang , Aonan Zhang , Quan Wang , Zhenyao Zhu
Abstract: A method includes receiving an utterance of speech and segmenting the utterance of speech into a plurality of segments. For each segment of the utterance of speech, the method also includes extracting a speaker=discriminative embedding from the segment and predicting a probability distribution over possible speakers for the segment using a probabilistic generative model configured to receive the extracted speaker-discriminative embedding as a feature input. The probabilistic generative model trained on a corpus of training speech utterances each segmented into a plurality of training segments. Each training segment including a corresponding speaker-discriminative embedding and a corresponding speaker label. The method also includes assigning a speaker label to each segment of the utterance of speech based on the probability distribution over possible speakers for the corresponding segment.
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公开(公告)号:US10403291B2
公开(公告)日:2019-09-03
申请号:US15995480
申请日:2018-06-01
Applicant: Google LLC
Inventor: Ignacio Lopez Moreno , Li Wan , Quan Wang
Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage medium, to facilitate language independent-speaker verification. In one aspect, a method includes actions of receiving, by a user device, audio data representing an utterance of a user. Other actions may include providing, to a neural network stored on the user device, input data derived from the audio data and a language identifier. The neural network may be trained using speech data representing speech in different languages or dialects. The method may include additional actions of generating, based on output of the neural network, a speaker representation and determining, based on the speaker representation and a second representation, that the utterance is an utterance of the user. The method may provide the user with access to the user device based on determining that the utterance is an utterance of the user.
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公开(公告)号:US20250095630A1
公开(公告)日:2025-03-20
申请号:US18966088
申请日:2024-12-02
Applicant: Google LLC
Inventor: Ye Jia , Zhifeng Chen , Yonghui Wu , Jonathan Shen , Ruoming Pang , Ron J. Weiss , Ignacio Lopez Moreno , Fei Ren , Yu Zhang , Quan Wang , Patrick An Phu Nguyen
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech synthesis. The methods, systems, and apparatus include actions of obtaining an audio representation of speech of a target speaker, obtaining input text for which speech is to be synthesized in a voice of the target speaker, generating a speaker vector by providing the audio representation to a speaker encoder engine that is trained to distinguish speakers from one another, generating an audio representation of the input text spoken in the voice of the target speaker by providing the input text and the speaker vector to a spectrogram generation engine that is trained using voices of reference speakers to generate audio representations, and providing the audio representation of the input text spoken in the voice of the target speaker for output.
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公开(公告)号:US12254891B2
公开(公告)日:2025-03-18
申请号:US17619648
申请日:2019-10-10
Applicant: GOOGLE LLC
Inventor: Quan Wang , Ignacio Lopez Moreno , Li Wan
IPC: G10L21/028 , G10L17/02 , G10L17/04 , G10L17/18 , G10L21/0232
Abstract: Processing of acoustic features of audio data to generate one or more revised versions of the acoustic features, where each of the revised versions of the acoustic features isolates one or more utterances of a single respective human speaker. Various implementations generate the acoustic features by processing audio data using portion(s) of an automatic speech recognition system. Various implementations generate the revised acoustic features by processing the acoustic features using a mask generated by processing the acoustic features and a speaker embedding for the single human speaker using a trained voice filter model. Output generated over the trained voice filter model is processed using the automatic speech recognition system to generate a predicted text representation of the utterance(s) of the single human speaker without reconstructing the audio data.
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公开(公告)号:US12154574B2
公开(公告)日:2024-11-26
申请号:US18506105
申请日:2023-11-09
Applicant: Google LLC
Inventor: Jason Pelecanos , Pu-sen Chao , Yiling Huang , Quan Wang
Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
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公开(公告)号:US12119014B2
公开(公告)日:2024-10-15
申请号:US17644108
申请日:2021-12-14
Applicant: Google LLC
Inventor: Arun Narayanan , Tom O'malley , Quan Wang , Alex Park , James Walker , Nathan David Howard , Yanzhang He , Chung-Cheng Chiu
IPC: G10L21/0216 , G06N3/04 , G10L15/06 , G10L21/0208 , H04R3/04
CPC classification number: G10L21/0216 , G06N3/04 , G10L15/063 , H04R3/04 , G10L2021/02082
Abstract: A method for automatic speech recognition using joint acoustic echo cancellation, speech enhancement, and voice separation includes receiving, at a contextual frontend processing model, input speech features corresponding to a target utterance. The method also includes receiving, at the contextual frontend processing model, at least one of a reference audio signal, a contextual noise signal including noise prior to the target utterance, or a speaker embedding including voice characteristics of a target speaker that spoke the target utterance. The method further includes processing, using the contextual frontend processing model, the input speech features and the at least one of the reference audio signal, the contextual noise signal, or the speaker embedding vector to generate enhanced speech features.
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公开(公告)号:US20240203426A1
公开(公告)日:2024-06-20
申请号:US18594833
申请日:2024-03-04
Applicant: GOOGLE LLC
Inventor: Quan Wang , Prashant Sridhar , Ignacio Lopez Moreno , Hannah Muckenhim
Abstract: Techniques are disclosed that enable processing of audio data to generate one or more refined versions of audio data, where each of the refined versions of audio data isolate one or more utterances of a single respective human speaker. Various implementations generate a refined version of audio data that isolates utterance(s) of a single human speaker by processing a spectrogram representation of the audio data (generated by processing the audio data with a frequency transformation) using a mask generated by processing the spectrogram of the audio data and a speaker embedding for the single human speaker using a trained voice filter model. Output generated over the trained voice filter model is processed using an inverse of the frequency transformation to generate the refined audio data.
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公开(公告)号:US11848002B2
公开(公告)日:2023-12-19
申请号:US17813361
申请日:2022-07-19
Applicant: Google LLC
Inventor: Ye Jia , Zhifeng Chen , Yonghui Wu , Jonathan Shen , Ruoming Pang , Ron J. Weiss , Ignacio Lopez Moreno , Fei Ren , Yu Zhang , Quan Wang , Patrick An Phu Nguyen
CPC classification number: G10L13/04 , G10L17/04 , G10L19/00 , G06N3/08 , G10L2013/021
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech synthesis. The methods, systems, and apparatus include actions of obtaining an audio representation of speech of a target speaker, obtaining input text for which speech is to be synthesized in a voice of the target speaker, generating a speaker vector by providing the audio representation to a speaker encoder engine that is trained to distinguish speakers from one another, generating an audio representation of the input text spoken in the voice of the target speaker by providing the input text and the speaker vector to a spectrogram generation engine that is trained using voices of reference speakers to generate audio representations, and providing the audio representation of the input text spoken in the voice of the target speaker for output.
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公开(公告)号:US11837238B2
公开(公告)日:2023-12-05
申请号:US17076743
申请日:2020-10-21
Applicant: Google LLC
Inventor: Jason Pelecanos , Pu-sen Chao , Yiling Huang , Quan Wang
Abstract: A method for evaluating a verification model includes receiving a first and a second set of verification results where each verification result indicates whether a primary model or an alternative model verifies an identity of a user as a registered user. The method further includes identifying each verification result in the first and second sets that includes a performance metric. The method also includes determining a first score of the primary model based on a number of the verification results identified in the first set that includes the performance metric and determining a second score of the alternative model based on a number of the verification results identified in the second set that includes the performance metric. The method further includes determining whether a verification capability of the alternative model is better than a verification capability of the primary model based on the first score and the second score.
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公开(公告)号:US11568878B2
公开(公告)日:2023-01-31
申请号:US17233253
申请日:2021-04-16
Applicant: Google LLC
Inventor: Rajeev Rikhye , Quan Wang , Yanzhang He , Qiao Liang , Ian C. McGraw
IPC: G10L17/24 , G10L17/06 , G10L21/028
Abstract: Techniques disclosed herein are directed towards streaming keyphrase detection which can be customized to detect one or more particular keyphrases, without requiring retraining of any model(s) for those particular keyphrase(s). Many implementations include processing audio data using a speaker separation model to generate separated audio data which isolates an utterance spoken by a human speaker from one or more additional sounds not spoken by the human speaker, and processing the separated audio data using a text independent speaker identification model to determine whether a verified and/or registered user spoke a spoken utterance captured in the audio data. Various implementations include processing the audio data and/or the separated audio data using an automatic speech recognition model to generate a text representation of the utterance. Additionally or alternatively, the text representation of the utterance can be processed to determine whether at least a portion of the text representation of the utterance captures a particular keyphrase. When the system determines the registered and/or verified user spoke the utterance and the system determines the text representation of the utterance captures the particular keyphrase, the system can cause a computing device to perform one or more actions corresponding to the particular keyphrase.
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