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公开(公告)号:US20220310062A1
公开(公告)日:2022-09-29
申请号:US17316198
申请日:2021-05-10
Applicant: Google LLC
Inventor: Tara Sainath , Arun Narayanan , Rami Botros , Yangzhang He , Ehsan Variani , Cyrill Allauzen , David Rybach , Ruorning Pang , Trevor Strohman
Abstract: An ASR model includes a first encoder configured to receive a sequence of acoustic frames and generate a first higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The ASR model also includes a second encoder configured to receive the first higher order feature representation generated by the first encoder at each of the plurality of output steps and generate a second higher order feature representation for a corresponding first higher order feature frame. The ASR model also includes a decoder configured to receive the second higher order feature representation generated by the second encoder at each of the plurality of output steps and generate a first probability distribution over possible speech recognition hypothesis. The ASR model also includes a language model configured to receive the first probability distribution over possible speech hypothesis and generate a rescored probability distribution.
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公开(公告)号:US11158321B2
公开(公告)日:2021-10-26
申请号:US16580726
申请日:2019-09-24
Applicant: Google LLC
Inventor: Asaf Aharoni , Arun Narayanan , Nir Shabat , Parisa Haghani , Galen Tsai Chuang , Yaniv Leviathan , Neeraj Gaur , Pedro J. Moreno Mengibar , Rohit Prakash Prabhavalkar , Zhongdi Qu , Austin Severn Waters , Tomer Amiaz , Michiel A. U. Bacchiani
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an automated calling system are disclosed. In one aspect, a method includes the actions of receiving audio data of an utterance spoken by a user who is having a telephone conversation with a bot. The actions further include determining a context of the telephone conversation. The actions further include determining a user intent of a first previous portion of the telephone conversation spoken by the user and a bot intent of a second previous portion of the telephone conversation outputted by a speech synthesizer of the bot. The actions further include, based on the audio data of the utterance, the context of the telephone conversation, the user intent, and the bot intent, generating synthesized speech of a reply by the bot to the utterance. The actions further include, providing, for output, the synthesized speech.
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公开(公告)号:US11062725B2
公开(公告)日:2021-07-13
申请号:US16278830
申请日:2019-02-19
Applicant: Google LLC
Inventor: Ehsan Variani , Kevin William Wilson , Ron J. Weiss , Tara N. Sainath , Arun Narayanan
IPC: G10L15/16 , G10L25/30 , G10L21/028 , G10L21/0388 , G10L19/008 , G10L15/20 , G10L21/0208 , G10L21/0216
Abstract: This specification describes computer-implemented methods and systems. One method includes receiving, by a neural network of 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 describe audio occurring at a same period of time. The method further includes generating, by a spatial filtering layer of the neural network, a spatial filtered output using the first data and the second data, and generating, by a spectral filtering layer of the neural network, a spectral filtered output using the spatial filtered output. Generating the spectral filtered output comprises processing frequency-domain data representing the spatial filtered output. The method still further includes processing, by one or more additional layers of 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:US10224058B2
公开(公告)日:2019-03-05
申请号:US15350293
申请日:2016-11-14
Applicant: Google LLC
Inventor: Ehsan Variani , Kevin William Wilson , Ron J. Weiss , Tara N. Sainath , Arun Narayanan
IPC: G10L15/16 , G10L25/30 , G10L21/028 , G10L21/0388 , G10L19/008 , G10L15/20 , G10L21/0208 , G10L21/0216
Abstract: This specification describes computer-implemented methods and systems. One method includes receiving, by a neural network of 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 describe audio occurring at a same period of time. The method further includes generating, by a spatial filtering layer of the neural network, a spatial filtered output using the first data and the second data, and generating, by a spectral filtering layer of the neural network, a spectral filtered output using the spatial filtered output. Generating the spectral filtered output comprises processing frequency-domain data representing the spatial filtered output. The method still further includes processing, by one or more additional layers of 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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