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公开(公告)号：US20240420686A1
公开(公告)日：2024-12-19
申请号：US18815200
申请日：2024-08-26
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Zhifeng Chen , Bo Li , Chung-Cheng Chiu , Kanury Kanishka Rao , Yonghui Wu , Ron J. Weiss , Navdeep Jaitly , Michiel A. U. Bacchiani , Tara N. Sainath , Jan Kazimierz Chorowski , Anjuli Patricia Kannan , Ekaterina Gonina , Patrick An Phu Nguyen
Abstract: A method for performing speech recognition using sequence-to-sequence models includes receiving audio data for an utterance and providing features indicative of acoustic characteristics of the utterance as input to an encoder. The method also includes processing an output of the encoder using an attender to generate a context vector, generating speech recognition scores using the context vector and a decoder trained using a training process, and generating a transcription for the utterance using word elements selected based on the speech recognition scores. The transcription is provided as an output of the ASR system.
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公开(公告)号：US11900915B2
公开(公告)日：2024-02-13
申请号：US17572238
申请日：2022-01-10
Applicant: Google LLC
Inventor： Zhifeng Chen , Bo Li , Eugene Weinstein , Yonghui Wu , Pedro J. Moreno Mengibar , Ron J. Weiss , Khe Chai Sim , Tara N. Sainath , Patrick An Phu Nguyen
CPC classification number: G10L15/005 , G10L15/07 , G10L15/16 , G10L2015/0631
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.
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公开(公告)号：US11238845B2
公开(公告)日：2022-02-01
申请号：US16684483
申请日：2019-11-14
Applicant: GOOGLE LLC
Inventor： Zhifeng Chen , Bo Li , Eugene Weinstein , Yonghui Wu , Pedro J. Moreno Mengibar , Ron J. Weiss , Khe Chai Sim , Tara N. Sainath , Patrick An Phu Nguyen
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.
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公开(公告)号：US20210358491A1
公开(公告)日：2021-11-18
申请号：US17443557
申请日：2021-07-27
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Tara N. Sainath , Yonghui Wu , Patrick An Phu Nguyen , Zhifeng Chen , Chung-Cheng Chiu , Anjuli Patricia Kannan
IPC: G10L15/197 , G10L15/16 , G10L15/06 , G10L15/02 , G10L15/22
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for speech recognition using attention-based sequence-to-sequence models. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A sequence of feature vectors indicative of the acoustic characteristics of the utterance is generated. The sequence of feature vectors is processed using a speech recognition model that has been trained using a loss function that uses N-best lists of decoded hypotheses, the speech recognition model including an encoder, an attention module, and a decoder. The encoder and decoder each include one or more recurrent neural network layers. A sequence of output vectors representing distributions over a predetermined set of linguistic units is obtained. A transcription for the utterance is obtained based on the sequence of output vectors. Data indicating the transcription of the utterance is provided.
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公开(公告)号：US11107463B2
公开(公告)日：2021-08-31
申请号：US16529252
申请日：2019-08-01
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Tara N. Sainath , Yonghui Wu , Patrick An Phu Nguyen , Zhifeng Chen , Chung-Cheng Chiu , Anjuli Patricia Kannan
IPC: G10L15/197 , G10L15/16 , G10L15/06 , G10L15/02 , G10L15/22
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-readable storage media, for speech recognition using attention-based sequence-to-sequence models. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A sequence of feature vectors indicative of the acoustic characteristics of the utterance is generated. The sequence of feature vectors is processed using a speech recognition model that has been trained using a loss function that uses N-best lists of decoded hypotheses, the speech recognition model including an encoder, an attention module, and a decoder. The encoder and decoder each include one or more recurrent neural network layers. A sequence of output vectors representing distributions over a predetermined set of linguistic units is obtained. A transcription for the utterance is obtained based on the sequence of output vectors. Data indicating the transcription of the utterance is provided.
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Patent Agency Ranking
公开(公告)号：US20200160836A1
公开(公告)日：2020-05-21
申请号：US16684483
申请日：2019-11-14
Applicant: GOOGLE LLC
Inventor： Zhifeng Chen , Bo Li , Eugene Weinstein , Yonghui Wu , Pedro J. Moreno Mengibar , Ron J. Weiss , Khe Chai Sim , Tara N. Sainath , Patrick An Phu Nguyen
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.
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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：US12106749B2
公开(公告)日：2024-10-01
申请号：US17448119
申请日：2021-09-20
Applicant: Google LLC
Inventor： Rohit Prakash Prabhavalkar , Zhifeng Chen , Bo Li , Chung-cheng Chiu , Kanury Kanishka Rao , Yonghui Wu , Ron J. Weiss , Navdeep Jaitly , Michiel A. u. Bacchiani , Tara N. Sainath , Jan Kazimierz Chorowski , Anjuli Patricia Kannan , Ekaterina Gonina , Patrick An Phu Nguyen
CPC classification number: G10L15/16 , G06N3/08 , G10L15/02 , G10L15/063 , G10L15/22 , G10L25/30 , G10L2015/025 , G10L15/26
Abstract: A method for performing speech recognition using sequence-to-sequence models includes receiving audio data for an utterance and providing features indicative of acoustic characteristics of the utterance as input to an encoder. The method also includes processing an output of the encoder using an attender to generate a context vector, generating speech recognition scores using the context vector and a decoder trained using a training process, and generating a transcription for the utterance using word elements selected based on the speech recognition scores. The transcription is provided as an output of the ASR system.
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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：US20220130374A1
公开(公告)日：2022-04-28
申请号：US17572238
申请日：2022-01-10
Applicant: Google LLC
Inventor： Zhifeng Chen , Bo Li , Eugene Weinstein , Yonghui Wu , Pedro J. Moreno Mengibar , Ron J. Weiss , Khe Chai Sim , Tara N. Sainath , Patrick An Phu Nguyen
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.
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