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公开(公告)号：US12277387B2
公开(公告)日：2025-04-15
申请号：US18056197
申请日：2022-11-16
Inventor： Ruiqing Zhang , Zhongjun He , Zhi Li , Hua Wu
IPC: G06F40/232 , G06F40/279 , G06F40/53
Abstract: A text processing method is provided. The method includes: a first probability value of each candidate character of a plurality of candidate characters corresponding to a target position is determined based on character feature information corresponding to the target position in a text fragment to be processed, wherein the character feature information is determined based on a context at the target position in the text fragment to be processed; a second probability value of each candidate character of the plurality of candidate characters is determined based on a character string including the candidate character and at least one character in at least one position in the text fragment to be processed adjacent to the target position; and a correction character at the target position is determined based on the first probability value and the second probability value of each candidate character of the plurality of candidate characters.
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公开(公告)号：US12265790B2
公开(公告)日：2025-04-01
申请号：US18053034
申请日：2022-11-07
Inventor： Ruiqing Zhang , Zhongjun He , Hua Wu
IPC: G06F40/279 , G06F40/166
Abstract: Disclosed are a method for correcting a text, an electronic device and a storage medium. The method includes: acquiring a text to be corrected; acquiring a phonetic symbol sequence of the text to be corrected; and obtaining a corrected text by inputting the text to be corrected and the phonetic symbol sequence into a text correction model, in which, the text correction model obtains the corrected text by: detecting an error word in the text to be corrected, determining a phonetic symbol corresponding to the error word in the phonetic symbol sequence, and adding the phonetic feature corresponding to the phonetic symbol behind the error word to obtain a phonetic symbol text, and correcting the error word and the phonetic feature in the phonetic symbol text to obtain the corrected text.
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公开(公告)号：US12282746B2
公开(公告)日：2025-04-22
申请号：US17820765
申请日：2022-08-18
Inventor： Haifeng Wang , Zhanyi Liu , Zhongjun He , Hua Wu , Zhi Li , Xing Wan , Jingxuan Zhao , Ruiqing Zhang , Chuanqiang Zhang , Fengtao Huang , Hanbing Song , Wei Di , Shuangshuang Cui , Yongzheng Xin
IPC: G06F40/58
Abstract: A display method, an electronic device, and a storage medium, which relate to a field of natural language processing and a field of display. The display method includes: acquiring a content to be displayed; extracting a target term from the content using a term extraction rule; acquiring an annotation information for at least one target term, responsive to an extraction of the at least one target term; and displaying the annotation information for the at least one target term and the content.
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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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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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Patent Agency Ranking
公开(公告)号：US20250054494A1
公开(公告)日：2025-02-13
申请号：US18930081
申请日：2024-10-29
Inventor： Pengzhi Gao , Ruiqing Zhang , Zhongjun He , Hua Wu
Abstract: A method for training a speech translation model includes: obtaining a trained first text translation model and a speech recognition model, and constructing a candidate speech translation model to be trained based on the first text translation model and the speech recognition model; obtaining at least one of a first sample source language speech or a first sample source language text to obtain a training sample of the candidate speech translation model; and training the candidate speech translation model based on the training sample until the training is completed, and obtaining a trained target speech translation model.
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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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8.发明申请公开(公告)号：US20250094739A1
公开(公告)日：2025-03-20
申请号：US18968830
申请日：2024-12-04
Inventor： Zhongjun He , Hua Wu , Haifeng Wang
Abstract: An information processing method. The method includes obtaining a first bilingual sentence pair, in which the first bilingual sentence pair comprises a source language sentence and a target language sentence; and obtaining a distilled second bilingual sentence pair by distilling a first language sentence in the first bilingual sentence pair based on a large language model (LLM), in which the first language sentence is the source language sentence or the target language sentence.
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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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