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Patent Agency Ranking
公开(公告)号：US20220083746A1
公开(公告)日：2022-03-17
申请号：US17459041
申请日：2021-08-27
Applicant: Google LLC
Inventor： 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
Abstract: 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.
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公开(公告)号：US11138392B2
公开(公告)日：2021-10-05
申请号：US16521780
申请日：2019-07-25
Applicant: Google LLC
Inventor： 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
Abstract: 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.
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公开(公告)号：US20200034436A1
公开(公告)日：2020-01-30
申请号：US16521780
申请日：2019-07-25
Applicant: Google LLC
Inventor： 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
Abstract: 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.
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公开(公告)号：US20240020491A1
公开(公告)日：2024-01-18
申请号：US18374071
申请日：2023-09-28
Applicant: Google LLC
Inventor： 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
Abstract: 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.
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公开(公告)号：US11809834B2
公开(公告)日：2023-11-07
申请号：US17459041
申请日：2021-08-27
Applicant: Google LLC
Inventor： 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
Abstract: 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.
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