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US Patent 11763098 System and method for language translation

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Contents

Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11763098
Patent Inventor Names
Jinnan Lu
Syed Salman Ali
Jie Ma
Zhanxuan Ding
Jason Cox
Renxian Zhang
Xun Li
Date of Patent
September 19, 2023
Patent Application Number
16939692
Date Filed
July 27, 2020
Patent Citations
‌
US Patent 10268685 Statistics-based machine translation method, apparatus and electronic device
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US Patent 10437933 Multi-domain machine translation system with training data clustering and dynamic domain adaptation
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US Patent 8805672 Translation cache prediction
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US Patent 9530416 System and method for managing models for embedded speech and language processing
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US Patent 9836457 Machine translation method for performing translation between languages
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US Patent 9910847 Language identification
Patent Citations Received
‌
US Patent 12067369 System and method for language translation
0
Patent Primary Examiner
‌
Edwin S Leland, III
CPC Code
‌
G06N 3/082
‌
G06N 3/086
‌
G06N 5/025
‌
G06N 7/005
‌
G06N 20/00
‌
G06F 40/20
‌
G06N 3/04
‌
G06F 40/51
...
Patent abstract

Provided are computer implemented systems and methods for providing improved language translation, including translation of input text to an output translated text element. This may include providing for rule-based language translation. This may further include a plurality of machine translation models adapted to different translation domains. A machine translation selector is described that selects an in-domain machine translator from the plurality of machine translation models based on an input text element. The selected in-domain machine translator may generate a first translated text element from the input text element. A post-editor module may generate a second translated text element by predicting a post-edit to the first translated text element. The first translated text element and the second translated text element are evaluated by a quality evaluation model that determines a first metric associated with the first translated text element and a second metric associated with the second text element.

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