Abstract
We propose an automatically word alignment method of Chinese-Vietnamese based on bidirectional RNN and linguistic features. With the bidirectional RNN, we can obtain the context information of both forward and backward direction. Moreover, some bilingual features are also integrated. In the process of training model. The experiments show that the approach proposed outperform the previous method, and suggests that linguistic features and context information can effectively enhance the effect of word alignment.
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Acknowledgment
This work was supported by the National Natural Science Foundation of China (Grant Nos.61761026, 61732005, 61672271, 61472168), the Natural Science Fundation of Yunnan Province (Grant No.2018FB104), Innovation Talent Fund For Technology of Yunnan Province (Grant No.2014HE001).
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Gao, S., Zhu, H., Wang, Z., Yu, Z., Wang, X. (2019). Chinese-Vietnamese Word Alignment Method Based on Bidirectional RNN and Linguistic Features. In: Sun, Y., Lu, T., Xie, X., Gao, L., Fan, H. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2018. Communications in Computer and Information Science, vol 917. Springer, Singapore. https://doi.org/10.1007/978-981-13-3044-5_33
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DOI: https://doi.org/10.1007/978-981-13-3044-5_33
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