- 专利标题: METHOD AND APPARATUS FOR TRAINING MODELS IN MACHINE TRANSLATION, ELECTRONIC DEVICE AND STORAGE MEDIUM
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申请号: US17200551申请日: 2021-03-12
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公开(公告)号: US20210390266A1公开(公告)日: 2021-12-16
- 发明人: Ruiqing Zhang , Chuanqiang Zhang , Zhongjun He , Zhi Li , Hua Wu
- 申请人: Beijing Baidu Netcom Science and Technology Co., Ltd.
- 申请人地址: CN Beijing
- 专利权人: Beijing Baidu Netcom Science and Technology Co., Ltd.
- 当前专利权人: Beijing Baidu Netcom Science and Technology Co., Ltd.
- 当前专利权人地址: CN Beijing
- 优先权: CN2020105505915 20200616
- 主分类号: G06F40/51
- IPC分类号: G06F40/51 ; G06F40/49 ; G06K9/62 ; G06F40/30 ; G06F40/44
摘要:
A method and apparatus for training models in machine translation, an electronic device and a storage medium are disclosed, which relates to the field of natural language processing technologies and the field of deep learning technologies. An implementation includes mining similar target sentences of a group of samples based on a parallel corpus using a machine translation model and a semantic similarity model, and creating a first training sample set; training the machine translation model with the first training sample set; mining a negative sample of each sample in the group of samples based on the parallel corpus using the machine translation model and the semantic similarity model, and creating a second training sample set; and training the semantic similarity model with the second sample training set. With the above-mentioned technical solution of the present application, by training the two models jointly, while the semantic similarity model is trained, the machine translation model may be optimized and nurtures the semantic similarity model, thus further improving the accuracy of the semantic similarity model.
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