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公开(公告)号：US20190197101A1
公开(公告)日：2019-06-27
申请号：US15852916
申请日：2017-12-22
申请人： Google LLC
发明人： Paul Roland Lambert , Timothy Youngjin Sohn , Jacqueline Amy Tsay , Gagan Bansal , Cole Austin Bevis , Kaushik Roy , Justin Tzi-jay LU , Katherine Anna Evans , Tobias Bosch , Yinan Wang , Matthew Vincent Dierker , Gregory Russell Bullock , Ettore Randazzo , Tobias Kaufmann , Yonghui Wu , Benjamin N. Lee , Xu Chen , Brian Strope , Yun-hsuan Sung , Do Kook Choe , Rami Eid Sammour Al-Rfou'
IPC分类号： G06F17/27 , G06F3/0484 , G06N99/00
CPC分类号： G06F17/276 , G06F3/0237 , G06F3/04842 , G06F17/273 , G06F17/274 , G06F17/277 , G06F17/2785 , G06F21/6245 , G06N20/00
摘要： A computing system is described that includes user interface components configured to receive typed user input; and one or more processors. The one or more processors are configured to: receive, by a computing system and at a first time, a first portion of text typed by a user in an electronic message being edited; predict, based on the first portion of text, a first candidate portion of text to follow the first portion of text; output, for display, the predicted first candidate portion of text for optional selection to append to the first portion of text; determine, at a second time that is after the first time, that the electronic message is directed to a sensitive topic; and responsive to determining that the electronic message is directed to a sensitive topic, refrain from outputting subsequent candidate portions of text for optional selection to append to text in the electronic message.
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公开(公告)号：US20220083746A1
公开(公告)日：2022-03-17
申请号：US17459041
申请日：2021-08-27
申请人： Google LLC
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
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.
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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
申请人： Google LLC
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
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.
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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
申请人： Google LLC
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
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.
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公开(公告)号：US20230385543A1
公开(公告)日：2023-11-30
申请号：US18447186
申请日：2023-08-09
申请人： Google LLC
发明人： Paul Roland Lambert , Timothy Youngjin Sohn , Jacqueline Amy Tsay , Gagan Bansal , Cole Austin Bevis , Kaushik Roy , Justin Tzi-jay LU , Katherine Anna Evans , Tobias Bosch , Yinan Wang , Matthew Vincent Dierker , Greg Russell Bullock , Ettore Randazzo , Tobias Kaufmann , Yonghui Wu , Benjamin N. Lee , Xu Chen , Brian Strope , Yun-hsuan Sung , Do Kook Choe , Rami Eid Sammour Al-Rfou'
IPC分类号： G06F40/274 , G06F3/04842 , G06N20/00 , G06F21/62 , G06F3/023 , G06F40/30 , G06F40/232 , G06F40/253 , G06F40/284
CPC分类号： G06F40/274 , G06F3/04842 , G06N20/00 , G06F21/6245 , G06F40/284 , G06F40/30 , G06F40/232 , G06F40/253 , G06F3/0237
摘要： A computing system is described that includes user interface components configured to receive typed user input; and one or more processors. The one or more processors are configured to: receive, by a computing system and at a first time, a first portion of text typed by a user in an electronic message being edited; predict, based on the first portion of text, a first candidate portion of text to follow the first portion of text; output, for display, the predicted first candidate portion of text for optional selection to append to the first portion of text; determine, at a second time that is after the first time, that the electronic message is directed to a sensitive topic; and responsive to determining that the electronic message is directed to a sensitive topic, refrain from outputting subsequent candidate portions of text for optional selection to append to text in the electronic message.
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公开(公告)号：US11755834B2
公开(公告)日：2023-09-12
申请号：US15852916
申请日：2017-12-22
申请人： Google LLC
发明人： Paul Roland Lambert , Timothy Youngjin Sohn , Jacqueline Amy Tsay , Gagan Bansal , Cole Austin Bevis , Kaushik Roy , Justin Tzi-jay Lu , Katherine Anna Evans , Tobias Bosch , Yinan Wang , Matthew Vincent Dierker , Gregory Russell Bullock , Ettore Randazzo , Tobias Kaufmann , Yonghui Wu , Benjamin N. Lee , Xu Chen , Brian Strope , Yun-hsuan Sung , Do Kook Choe , Rami Eid Sammouf Al-Rfou'
IPC分类号： G06F40/274 , G06F3/04842 , G06N20/00 , G06F21/62 , G06F3/023 , G06F40/30 , G06F40/232 , G06F40/253 , G06F40/284
CPC分类号： G06F40/274 , G06F3/0237 , G06F3/04842 , G06F21/6245 , G06F40/232 , G06F40/253 , G06F40/284 , G06F40/30 , G06N20/00
摘要： A computing system is described that includes user interface components configured to receive typed user input; and one or more processors. The one or more processors are configured to: receive, by a computing system and at a first time, a first portion of text typed by a user in an electronic message being edited; predict, based on the first portion of text, a first candidate portion of text to follow the first portion of text; output, for display, the predicted first candidate portion of text for optional selection to append to the first portion of text; determine, at a second time that is after the first time, that the electronic message is directed to a sensitive topic; and responsive to determining that the electronic message is directed to a sensitive topic, refrain from outputting subsequent candidate portions of text for optional selection to append to text in the electronic message.
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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
申请人： Google LLC
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
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.
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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
申请人： Google LLC
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
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.
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