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公开(公告)号：US20220351713A1
公开(公告)日：2022-11-03
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
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：US11488575B2
公开(公告)日：2022-11-01
申请号：US17055951
申请日：2019-05-17
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 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：US20240339106A1
公开(公告)日：2024-10-10
申请号：US18746809
申请日：2024-06-18
Applicant: Google LLC
Inventor： Ye Jia , Byungha Chun , Yu Zhang , Jonathan Shen , Yonghui Wu
IPC: G10L13/08 , G06F40/263 , G06F40/279 , G06N3/08 , G10L13/047
CPC classification number: G10L13/086 , G06F40/263 , G06F40/279 , G06N3/08 , G10L13/047
Abstract: A method includes receiving a text input including a sequence of words represented as an input encoder embedding. The input encoder embedding includes a plurality of tokens, with the plurality of tokens including a first set of grapheme tokens representing the text input as respective graphemes and a second set of phoneme tokens representing the text input as respective phonemes. The method also includes, for each respective phoneme token of the second set of phoneme tokens: identifying a respective word of the sequence of words corresponding to the respective phoneme token and determining a respective grapheme token representing the respective word of the sequence of words corresponding to the respective phoneme token. The method also includes generating an output encoder embedding based on a relationship between each respective phoneme token and the corresponding grapheme token determined to represent a same respective word as the respective phoneme token.
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公开(公告)号：US12020685B2
公开(公告)日：2024-06-25
申请号：US17643684
申请日：2021-12-10
Applicant: Google LLC
Inventor： Ye Jia , Byungha Chun , Yu Zhang , Jonathan Shen , Yonghui Wu
IPC: G10L13/08 , G06F40/263 , G06F40/279 , G06N3/08 , G10L13/047
CPC classification number: G10L13/086 , G06F40/263 , G06F40/279 , G06N3/08 , G10L13/047
Abstract: A method includes receiving a text input including a sequence of words represented as an input encoder embedding. The input encoder embedding includes a plurality of tokens, with the plurality of tokens including a first set of grapheme tokens representing the text input as respective graphemes and a second set of phoneme tokens representing the text input as respective phonemes. The method also includes, for each respective phoneme token of the second set of phoneme tokens: identifying a respective word of the sequence of words corresponding to the respective phoneme token and determining a respective grapheme token representing the respective word of the sequence of words corresponding to the respective phoneme token. The method also includes generating an output encoder embedding based on a relationship between each respective phoneme token and the corresponding grapheme token determined to represent a same respective word as the respective phoneme token.
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公开(公告)号：US11335321B2
公开(公告)日：2022-05-17
申请号：US17005974
申请日：2020-08-28
Applicant: Google LLC
Inventor： Ye Jia , Byungha Chun , Yusuke Oda , Norman Casagrande , Tejas Iyer , Fan Luo , Russell John Wyatt Skerry-Ryan , Jonathan Shen , Yonghui Wu , Yu Zhang
IPC: G10L13/08 , G10L13/04 , G10L13/033 , G10L15/06
Abstract: A method of building a text-to-speech (TTS) system from a small amount of speech data includes receiving a first plurality of recorded speech samples from an assortment of speakers and a second plurality of recorded speech samples from a target speaker where the assortment of speakers does not include the target speaker. The method further includes training a TTS model using the first plurality of recorded speech samples from the assortment of speakers. Here, the trained TTS model is configured to output synthetic speech as an audible representation of a text input. The method also includes re-training the trained TTS model using the second plurality of recorded speech samples from the target speaker combined with the first plurality of recorded speech samples from the assortment of speakers. Here, the re-trained TTS model is configured to output synthetic speech resembling speaking characteristics of the target speaker.
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Patent Agency Ranking
公开(公告)号：US20220122582A1
公开(公告)日：2022-04-21
申请号：US17327076
申请日：2021-05-21
Applicant: Google LLC
Inventor： Isaac Elias , Jonathan Shen , Yu Zhang , Ye Jia , Ron J. Weiss , Yonghui Wu , Byungha Chun
IPC: G10L13/08 , G10L21/10 , G06F40/126 , G06N3/08
Abstract: A method for training a non-autoregressive TTS model includes receiving training data that includes a reference audio signal and a corresponding input text sequence. The method also includes encoding the reference audio signal into a variational embedding that disentangles the style/prosody information from the reference audio signal and encoding the input text sequence into an encoded text sequence. The method also includes predicting a phoneme duration for each phoneme in the input text sequence and determining a phoneme duration loss based on the predicted phoneme durations and a reference phoneme duration. The method also includes generating one or more predicted mel-frequency spectrogram sequences for the input text sequence and determining a final spectrogram loss based on the predicted mel-frequency spectrogram sequences and a reference mel-frequency spectrogram sequence. The method also includes training the TTS model based on the final spectrogram loss and the corresponding phoneme duration loss.
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公开(公告)号：US20210217404A1
公开(公告)日：2021-07-15
申请号：US17055951
申请日：2019-05-17
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 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：US20200051583A1
公开(公告)日：2020-02-13
申请号：US16058640
申请日：2018-08-08
Applicant: Google LLC
Inventor： Yonghui Wu , Jonathan Shen , Ruoming Pang , Ron J. Weiss
Abstract: Methods, systems, and computer program products for generating, from an input character sequence, an output sequence of audio data representing the input character sequence. The output sequence of audio data includes a respective audio output sample for each of a number of time steps. One example method includes, for each of the time steps: generating a mel-frequency spectrogram for the time step by processing a representation of a respective portion of the input character sequence using a decoder neural network; generating a probability distribution over a plurality of possible audio output samples for the time step by processing the mel-frequency spectrogram for the time step using a vocoder neural network; and selecting the audio output sample for the time step from the possible audio output samples in accordance with the probability distribution.
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公开(公告)号：US12148444B2
公开(公告)日：2024-11-19
申请号：US17222736
申请日：2021-04-05
Applicant: Google LLC
Inventor： Yonghui Wu , Jonathan Shen , Ruoming Pang , Ron J. Weiss , Michael Schuster , Navdeep Jaitly , Zongheng Yang , Zhifeng Chen , Yu Zhang , Yuxuan Wang , Russell John Wyatt Skerry-Ryan , Ryan M. Rifkin , Ioannis Agiomyrgiannakis
Abstract: Methods, systems, and computer program products for generating, from an input character sequence, an output sequence of audio data representing the input character sequence. The output sequence of audio data includes a respective audio output sample for each of a number of time steps. One example method includes, for each of the time steps: generating a mel-frequency spectrogram for the time step by processing a representation of a respective portion of the input character sequence using a decoder neural network; generating a probability distribution over a plurality of possible audio output samples for the time step by processing the mel-frequency spectrogram for the time step using a vocoder neural network; and selecting the audio output sample for the time step from the possible audio output samples in accordance with the probability distribution.
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公开(公告)号：US12100382B2
公开(公告)日：2024-09-24
申请号：US17492543
申请日：2021-10-01
Applicant: Google LLC
Inventor： Yu Zhang , Isaac Elias , Byungha Chun , Ye Jia , Yonghui Wu , Mike Chrzanowski , Jonathan Shen
IPC: G10L13/027 , G10L13/04
CPC classification number: G10L13/027 , G10L13/04
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, synthesizing audio data from text data using duration prediction. One of the methods includes processing an input text sequence that includes a respective text element at each of multiple input time steps using a first neural network to generate a modified input sequence comprising, for each input time step, a representation of the corresponding text element in the input text sequence; processing the modified input sequence using a second neural network to generate, for each input time step, a predicted duration of the corresponding text element in the output audio sequence; upsampling the modified input sequence according to the predicted durations to generate an intermediate sequence comprising a respective intermediate element at each of a plurality of intermediate time steps; and generating an output audio sequence using the intermediate sequence.
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