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    Large-scale multilingual speech recognition with a streaming end-to-end model
    11.
    发明授权
    Large-scale multilingual speech recognition with a streaming end-to-end model 有权

    公开(公告)号：US11468244B2

    公开(公告)日：2022-10-11

    申请号：US16834342

    申请日：2020-03-30

    Applicant: Google LLC

    Inventor： Anjuli Patricia Kannan ,  Tara N. Sainath ,  Yonghui Wu ,  Ankur Bapna ,  Arindrima Datta

    IPC: G10L15/00 ,  G06F40/40

    Abstract: A method of transcribing speech using a multilingual end-to-end (E2E) speech recognition model includes receiving audio data for an utterance spoken in a particular native language, obtaining a language vector identifying the particular language, and processing, using the multilingual E2E speech recognition model, the language vector and acoustic features derived from the audio data to generate a transcription for the utterance. The multilingual E2E speech recognition model includes a plurality of language-specific adaptor modules that include one or more adaptor modules specific to the particular native language and one or more other adaptor modules specific to at least one other native language different than the particular native language. The method also includes providing the transcription for output.

    Unsupervised Parallel Tacotron Non-Autoregressive and Controllable Text-To-Speech
    12.
    发明申请
    Unsupervised Parallel Tacotron Non-Autoregressive and Controllable Text-To-Speech 有权

    公开(公告)号：US20220301543A1

    公开(公告)日：2022-09-22

    申请号：US17326542

    申请日：2021-05-21

    Applicant: Google LLC

    Inventor： Isaac Elias ,  Byungha Chun ,  Jonathan Shen ,  Ye Jia ,  Yu Zhang ,  Yonghui Wu

    IPC: G10L13/08 ,  G10L13/04

    Abstract: A method for training a non-autoregressive TTS model includes obtaining a sequence representation of an encoded text sequence concatenated with a variational embedding. The method also includes using a duration model network to predict a phoneme duration for each phoneme represented by the encoded text sequence. Based on the predicted phoneme durations, the method also includes learning an interval representation and an auxiliary attention context representation. The method also includes upsampling, using the interval representation and the auxiliary attention context representation, the sequence representation into an upsampled output specifying a number of frames. The method also includes generating, based on the upsampled output, one or more predicted mel-frequency spectrogram sequences for the encoded text sequence. The method also includes determining a final spectrogram loss based on the predicted mel-frequency spectrogram sequences and a reference mel-frequency spectrogram sequence and training the TTS model based on the final spectrogram loss.

    NEURAL MACHINE TRANSLATION SYSTEMS
    14.
    发明申请
    NEURAL MACHINE TRANSLATION SYSTEMS 有权

    公开(公告)号：US20210390271A1

    公开(公告)日：2021-12-16

    申请号：US17459111

    申请日：2021-08-27

    Applicant: Google LLC

    Inventor： Mohammad Norouzi ,  Zhifeng Chen ,  Yonghui Wu ,  Michael Schuster ,  Quoc V. Le

    IPC: G06F40/58 ,  G06F40/44 ,  G06N3/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for neural machine translation. The method comprises obtaining a first sequence of words in a source language, generating a modified sequence of words in the source language by inserting a word boundary symbol only at the beginning of each word in the first sequence of words and not at the end of each word, dividing the modified sequence of words into wordpieces using a wordpiece model, generating, from the wordpieces, an input sequence of input tokens for a neural machine translation system; and generating an output sequence of words using the neural machine translation system based on the input sequence of input tokens.

    Text-to-speech using duration prediction
    18.
    发明授权
    Text-to-speech using duration prediction 有权

    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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