Abstract
The lack of Chinese-Vietnamese parallel corpus has resulted in poor translation of Chinese-Vietnamese neural machine translation. In order to solve this problem, we propose a phrase-based Chinese-Vietnamese pseudo-parallel sentence pair generation method. This method expands the corpus of Chinese-Vietnamese neural machine translation and improves the performance of Chinese-Vietnamese neural machine translation. Firstly, based on the small-scale Chinese-Vietnamese parallel corpus, the method selects the phrase module according to the phrase syntactic structure information. Then this method combines word alignment information with replacement rules. Finally, the method achieves the expansion of Chinese-Vietnamese pseudo-parallel corpus. Experiments show that this method can effectively generate Chinese-Vietnamese pseudo-parallel sentence pairs and improve the performance of Chinese-Vietnamese neural machine translation.
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Acknowledgements
The work was supported by National key research and development plan project (Grant Nos. 2018YFC0830105, 2018YFC0830100), National Natural Science Foundation of China (Grant Nos. 61732005, 61672271, 61761026, and 61762056), Yunnan high-tech industry development project (Grant No. 201606), and Natural Science Foundation of Yunnan Province (Grant No. 2018FB104).
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Zhai, J., Yu, Z., Gao, S., Wang, Z., Pu, L. (2019). Phrase-Based Chinese-Vietnamese Pseudo-Parallel Sentence Pair Generation. In: Huang, S., Knight, K. (eds) Machine Translation. CCMT 2019. Communications in Computer and Information Science, vol 1104. Springer, Singapore. https://doi.org/10.1007/978-981-15-1721-1_6
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DOI: https://doi.org/10.1007/978-981-15-1721-1_6
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