The problem of rare and unknown words is an important issue in Uyghur-Chinese machine translation, especially using neural machine translation model. We propose a novel way to deal with the rare and unknown words. Based on neural machine translation of using pointers over input sequence, our approach which consists of preprocess and post-process can be used in all neural machine translation model. Pre-process modify the Uyghur-Chinese corpus to extend the ability of pointer network, and the post- process retranslating the raw translation by a phrase-based machine translation model or a wordlist. Experiment show that neural machine translation model used the approach proposed by this paper get a higher BLEU score than the phrase-based model in Uyghur-Chinese MT.
CITATION STYLE
Kong, J., Yang, Y., Zhou, X., Wang, L., & Li, X. (2016). Research for Uyghur-Chinese neural machine translation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10102, pp. 141–152). Springer Verlag. https://doi.org/10.1007/978-3-319-50496-4_12
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