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    Speech recognition using convolutional neural networks
    14.
    发明授权
    Speech recognition using convolutional neural networks 有权

    公开(公告)号：US11069345B2

    公开(公告)日：2021-07-20

    申请号：US16719424

    申请日：2019-12-18

    Applicant: DeepMind Technologies Limited

    Inventor： Aaron Gerard Antonius van den Oord ,  Sander Etienne Lea Dieleman ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Oriol Vinyals ,  Lasse Espeholt

    IPC: G10L15/16 ,  G06N3/04 ,  G06N3/08 ,  G10L15/02 ,  G10L15/22

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing speech recognition by generating a neural network output from an audio data input sequence, where the neural network output characterizes words spoken in the audio data input sequence. One of the methods includes, for each of the audio data inputs, providing a current audio data input sequence that comprises the audio data input and the audio data inputs preceding the audio data input in the audio data input sequence to a convolutional subnetwork comprising a plurality of dilated convolutional neural network layers, wherein the convolutional subnetwork is configured to, for each of the plurality of audio data inputs: receive the current audio data input sequence for the audio data input, and process the current audio data input sequence to generate an alternative representation for the audio data input.

    Sample-efficient adaptive text-to-speech
    15.
    发明授权
    Sample-efficient adaptive text-to-speech 有权

    公开(公告)号：US10810993B2

    公开(公告)日：2020-10-20

    申请号：US16666043

    申请日：2019-10-28

    Applicant: DeepMind Technologies Limited

    Inventor： Yutian Chen ,  Scott Ellison Reed ,  Aaron Gerard Antonius van den Oord ,  Oriol Vinyals ,  Heiga Zen ,  Ioannis Alexandros Assael ,  Brendan Shillingford ,  Joao Ferdinando Gomes de Freitas

    IPC: G10L13/047 ,  G06N3/08 ,  G10L13/033 ,  G10L13/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an adaptive audio-generation model. One of the methods includes generating an adaptive audio-generation model including learning a plurality of embedding vectors and parameter values of a neural network using training data comprising first text and audio data representing a plurality of different individual speakers speaking portions of the first text, wherein the plurality of embedding vectors represent respective voice characteristics of the plurality of different individual speakers. The adaptive audio-generation model is adapted for a new individual speaker using adaptation data comprising second text and audio data representing the new individual speaker speaking portions of the second text, the new individual speaker being different from each of the plurality of individual speakers, wherein adapting the audio-generation model includes learning a new embedding vector for the new individual speaker.

    Speech recognition using convolutional neural networks
    16.
    发明授权
    Speech recognition using convolutional neural networks 有权

    公开(公告)号：US10586531B2

    公开(公告)日：2020-03-10

    申请号：US16209661

    申请日：2018-12-04

    Applicant: DeepMind Technologies Limited

    Inventor： Aaron Gerard Antonius van den Oord ,  Sander Etienne Lea Dieleman ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Oriol Vinyals ,  Lasse Espeholt

    IPC: G10L15/16 ,  G06N3/04 ,  G10L15/02 ,  G10L15/22 ,  G06N3/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing speech recognition by generating a neural network output from an audio data input sequence, where the neural network output characterizes words spoken in the audio data input sequence. One of the methods includes, for each of the audio data inputs, providing a current audio data input sequence that comprises the audio data input and the audio data inputs preceding the audio data input in the audio data input sequence to a convolutional subnetwork comprising a plurality of dilated convolutional neural network layers, wherein the convolutional subnetwork is configured to, for each of the plurality of audio data inputs: receive the current audio data input sequence for the audio data input, and process the current audio data input sequence to generate an alternative representation for the audio data input.

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