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An Efficient Method for Generating Synthetic Data for Low-Resource Machine Translation: An empirical study of Chinese, Japanese to Vietnamese Neural Machine Translation.

, , , , and . Appl. Artif. Intell., (2022)

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Overcoming the Rare Word Problem for low-resource language pairs in Neural Machine Translation., , , and . WAT@EMNLP-IJCNLP, page 207-214. Association for Computational Linguistics, (2019)A Simple and Fast Strategy for Handling Rare Words in Neural Machine Translation., , and . AACL/IJCNLP 2022 (Student Research Workshop), page 40-46. Association for Computational Linguistics, (2022)Improving Multilingual Neural Machine Translation For Low-Resource Languages: French-, English- Vietnamese., , , , and . CoRR, (2020)An Efficient Method for Generating Synthetic Data for Low-Resource Machine Translation: An empirical study of Chinese, Japanese to Vietnamese Neural Machine Translation., , , , and . Appl. Artif. Intell., (2022)Improving Multilingual Neural Machine Translation with Artificial Labels., , , and . SoICT, page 79-84. ACM, (2023)ViNMT: Neural Machine Translation Tookit., , , , , , and . CoRR, (2021)How Transformer Revitalizes Character-based Neural Machine Translation: An Investigation on Japanese-Vietnamese Translation Systems., , , and . IWSLT, Association for Computational Linguistics, (2019)Combining Advanced Methods in Japanese-Vietnamese Neural Machine Translation., , , and . KSE, page 318-322. IEEE, (2018)