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公开(公告)号：US20230015313A1
公开(公告)日：2023-01-19
申请号：US17656160
申请日：2022-03-23
Inventor： Chuanqiang Zhang , Ruiqing Zhang , Zhongjun He , Zhi Li , Hua Wu
IPC: G06F40/58 , G06F40/279
Abstract: Disclosed are a translation method, a classification model training method, a device and a storage medium, which relate to the field of computer technologies, particularly to the field of artificial intelligence such as natural language processing and deep learning. The translation method includes: obtaining a current processing unit of a source language text based on a segmented word in the source language text; determining a classification result of the current processing unit with a classification model; and in response to determining that the classification result is the current processing unit being translatable separately, translating the current processing unit to obtain translation result in a target language corresponding to the current processing unit.
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Patent Agency Ranking
公开(公告)号：US12236203B2
公开(公告)日：2025-02-25
申请号：US17951216
申请日：2022-09-23
Inventor： Ruiqing Zhang , Xiyang Wang , Hui Liu , Zhongjun He , Zhi Li , Hua Wu
Abstract: A translation method, a model training method, apparatuses, electronic devices and storage mediums, which relate to the field of artificial intelligence technologies, such as machine learning technologies, information processing technologies, are disclosed. In an implementation, a weight for each translation model in at least two pre-trained translation models translating a to-be-translated specified sentence is acquired based on the specified sentence and a pre-trained weighting model; and the specified sentence is translating using the at least two translation models based on the weight for each translation model translating the specified sentence.
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公开(公告)号：US20220391594A1
公开(公告)日：2022-12-08
申请号：US17820768
申请日：2022-08-18
Inventor： Haifeng Wang , Zhongjun He , Hua Wu , Zhanyi Liu , Zhi Li , Xing Wan , Jingxuan Zhao , Ruiqing Zhang , Chuanqiang Zhang , Fengtao Huang , Shuangshuang Cui , Yongzheng Xin
IPC: G06F40/30 , G06F40/58 , H04N5/278 , G06F40/166 , G06F40/279 , G06N5/02
Abstract: A display method, a method of training a semantic unit detection model, an electronic device, and a storage medium, which relate to a field of artificial intelligence technology, in particular to fields of natural language processing and machine translation technologies. The display method includes: acquiring a language sequence to be displayed; dividing the language sequence to be displayed into a plurality of semantic units with semantics; and converting the plurality of semantic units into subtitles for display one by one.
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公开(公告)号：US12210956B2
公开(公告)日：2025-01-28
申请号：US18074853
申请日：2022-12-05
Inventor： Ruiqing Zhang , Hui Liu , Zhongjun He , Zhi Li , Hua Wu
Abstract: The present disclosure provides a translation method and apparatus, an electronic device, and a non-transitory storage medium. An implementation includes: determining an encoded feature of a sentence to be translated by an encoding module; determining, by a graph network module, a knowledge fusion feature of the sentence to be translated based on a preset graph network, wherein the preset graph network is constructed based on a polysemous word in a source language corresponding to the sentence to be translated and a plurality of translated words corresponding to the polysemous word in a target language; determining, by a decoding network, a translated sentence corresponding to the sentence to be translated based on the encoded feature and the knowledge fusion feature.
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公开(公告)号：US12197882B2
公开(公告)日：2025-01-14
申请号：US17885152
申请日：2022-08-10
Inventor： Ruiqing Zhang , Xiyang Wang , Zhongjun He , Zhi Li , Hua Wu
IPC: G06F40/58
Abstract: A translation method, an electronic device and a storage medium, which relate to the field of artificial intelligence technologies, such as machine learning technologies, information processing technologies, are disclosed. An implementation includes: acquiring an intermediate translation result generated by each of multiple pre-trained translation models for a to-be-translated specified sentence in a same iteration of a translation process, so as to obtain multiple intermediate translation results; acquiring a co-occurrence word based on the multiple intermediate translation results; and acquiring a target translation result of the specified sentence based on the co-occurrence word.
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6.发明公开公开(公告)号：US20230267286A1
公开(公告)日：2023-08-24
申请号：US17879965
申请日：2022-08-03
Inventor： Liwen Zhang , Meng Sun , Zhongjun He , Zhi Li
IPC: G06F40/58 , G06F40/211
CPC classification number: G06F40/58 , G06F40/211
Abstract: Provided are a translation model training method, a translation method, a device, and a storage medium, and relates to a field of computer technology, and in particular, to artificial intelligence fields such as natural language processing, machine translation and the like. The translation model training method includes: processing a sample document, to obtain an RST discourse structure tree in a dependency form of the sample document, a side in the RST discourse structure tree in the dependency form indicating an RST relationship in a discourse of the sample document; determining an attention mechanism of a translation model to be trained, based on the RST relationship in the RST discourse structure tree in the dependency form; and inputting the RST discourse structure tree in the dependency form and the sample document into the translation model to be trained for training, to obtain a trained translation model.
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