- 专利标题: MACHINE TRANSLATION USING NEURAL NETWORK MODELS
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申请号: US17459041申请日: 2021-08-27
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公开(公告)号: US20220083746A1公开(公告)日: 2022-03-17
- 发明人: Zhifeng Chen , Macduff Richard Hughes , Yonghui Wu , Michael Schuster , Xu Chen , Llion Owen Jones , Niki J. Parmar , George Foster , Orhan Firat , Ankur Bapna , Wolfgang Macherey , Melvin Jose Johnson Premkumar
- 申请人: Google LLC
- 申请人地址: US CA Mountain View
- 专利权人: Google LLC
- 当前专利权人: Google LLC
- 当前专利权人地址: US CA Mountain View
- 主分类号: G06F40/58
- IPC分类号: G06F40/58 ; G06N3/08
摘要:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine translation using neural networks. In some implementations, a text in one language is translated into a second language using a neural network model. The model can include an encoder neural network comprising a plurality of bidirectional recurrent neural network layers. The encoding vectors are processed using a multi-headed attention module configured to generate multiple attention context vectors for each encoding vector. A decoder neural network generates a sequence of decoder output vectors using the attention context vectors. The decoder output vectors can represent distributions over various language elements of the second language, allowing a translation of the text into the second language to be determined based on the sequence of decoder output vectors.
公开/授权文献
- US11809834B2 Machine translation using neural network models 公开/授权日:2023-11-07
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