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- W4386858705 abstract "Mongolian-Chinese neural machine translation has the problem that it cannot make full use of context information for document-level translation. In order to solve this problem, a Mongolian-Chinese neural machine translation model using the context information of the passage is proposed.The model makes better use of context information for document-level translation by introducing local encoders and global encoders in the encoder and caching mechanisms in the decoder. Through experiments, the document-level Mongolian-Chinese machine translation model integrated with context information is compared with the sentence-level Mongolian-Chinese machine translation model based on Transformer. The experimental results verify the advantages of the document-level Mongolian-Chinese machine translation model integrated with context information in translation performance." @default.
- W4386858705 created "2023-09-20" @default.
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- W4386858705 date "2023-04-21" @default.
- W4386858705 modified "2023-10-08" @default.
- W4386858705 title "Mongolian-Chinese Machine Translation Based on Text Context Information" @default.
- W4386858705 cites W2971278086 @default.
- W4386858705 doi "https://doi.org/10.1109/icsp58490.2023.10248785" @default.
- W4386858705 hasPublicationYear "2023" @default.
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