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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：US20210366463A1
公开(公告)日：2021-11-25
申请号：US17391799
申请日：2021-08-02
Applicant: Google LLC
Inventor： Samuel Bengio , Yuxuan Wang , Zongheng Yang , Zhifeng Chen , Yonghui Wu , Ioannis Agiomyrgiannakis , Ron J. Weiss , Navdeep Jaitly , Ryan M. Rifkin , Robert Andrew James Clark , Quoc V. Le , Russell J. Ryan , Ying Xiao
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.
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公开(公告)号：US10930270B2
公开(公告)日：2021-02-23
申请号：US16541982
申请日：2019-08-15
Applicant: Google LLC
Inventor： Tara N. Sainath , Ron J. Weiss , Andrew W. Senior , Kevin William Wilson
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing audio waveforms. In some implementations, a time-frequency feature representation is generated based on audio data. The time-frequency feature representation is input to an acoustic model comprising a trained artificial neural network. The trained artificial neural network comprising a frequency convolution layer, a memory layer, and one or more hidden layers. An output that is based on output of the trained artificial neural network is received. A transcription is provided, where the transcription is determined based on the output of the acoustic model.
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公开(公告)号：US20200098350A1
公开(公告)日：2020-03-26
申请号：US16696101
申请日：2019-11-26
Applicant: Google LLC
Inventor： Samuel Bengio , Yuxuan Wang , Zongheng Yang , Zhifeng Chen , Yonghui Wu , Ioannis Agiomyrgiannakis , Ron J. Weiss , Navdeep Jaitly , Ryan M. Rifkin , Robert Andrew James Clark , Quoc V. Le , Russell J. Ryan , Ying Xiao
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.
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Patent Agency Ranking
公开(公告)号：US20200027444A1
公开(公告)日：2020-01-23
申请号：US16516390
申请日：2019-07-19
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: Methods, systems, and apparatus, including computer-readable media, for performing speech recognition using sequence-to-sequence models. An automated speech recognition (ASR) system receives audio data for an utterance and provides features indicative of acoustic characteristics of the utterance as input to an encoder. The system processes an output of the encoder using an attender to generate a context vector and generates speech recognition scores using the context vector and a decoder trained using a training process that selects at least one input to the decoder with a predetermined probability. An input to the decoder during training is selected between input data based on a known value for an element in a training example, and input data based on an output of the decoder for the element in the training example. A transcription is generated 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：US20190311708A1
公开(公告)日：2019-10-10
申请号：US16447862
申请日：2019-06-20
Applicant: Google LLC
Inventor： Samy Bengio , Yuxuan Wang , Zongheng Yang , Zhifeng Chen , Yonghui Wu , Ioannis Agiomyrgiannakis , Ron J. Weiss , Navdeep Jaitly , Ryan M. Rifkin , Robert Andrew James Clark , Quoc V. Le , Russell J. Ryan , Ying Xiao
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.
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公开(公告)号：US10339921B2
公开(公告)日：2019-07-02
申请号：US14987146
申请日：2016-01-04
Applicant: Google LLC
Inventor： Tara N. Sainath , Ron J. Weiss , Kevin William Wilson
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using neural networks. One of the methods includes receiving, by a neural network in a speech recognition system, first data representing a first raw audio signal and second data representing a second raw audio signal, the first raw audio signal and the second raw audio signal for the same period of time, generating, by a spatial filtering convolutional layer in the neural network, a spatial filtered output the first data and the second data, generating, by a spectral filtering convolutional layer in the neural network, a spectral filtered output using the spatial filtered output, and processing, by one or more additional layers in the neural network, the spectral filtered output to predict sub-word units encoded in both the first raw audio signal and the second raw audio signal.
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公开(公告)号：US20180197534A1
公开(公告)日：2018-07-12
申请号：US15848829
申请日：2017-12-20
Applicant: Google LLC
Inventor： Bo Li , Ron J. Weiss , Michiel A.U. Bacchiani , Tara N. Sainath , Kevin William Wilson
IPC: G10L15/16 , G10L21/0224 , G10L15/26 , G10L21/0216
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural network adaptive beamforming for multichannel speech recognition are disclosed. In one aspect, a method includes the actions of receiving a first channel of audio data corresponding to an utterance and a second channel of audio data corresponding to the utterance. The actions further include generating a first set of filter parameters for a first filter based on the first channel of audio data and the second channel of audio data and a second set of filter parameters for a second filter based on the first channel of audio data and the second channel of audio data. The actions further include generating a single combined channel of audio data. The actions further include inputting the audio data to a neural network. The actions further include providing a transcription for the utterance.
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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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