JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (1): 77-83.doi: 10.6040/j.issn.1671-9352.3.2014.289

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A bilingual word alignment method of Vietnamese-Chinese based on deep neural network

MO Yuan-yuan1, GUO Jian-yi1,2*, YU Zheng-tao1,2, MAO Cun-li1,2, NIU Yi-tong1   

  1. 1. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650051, Yunnan, China;
    2. Intelligent Information Processing Key Laboratory, Kunming University of Science and Technology, Kunming 650051, Yunnan, China
  • Received:2015-03-03 Online:2016-01-16 Published:2016-11-29

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Abstract: It is difficult to achieve auto-alignment between Vietnamese and Chinese, because their syntax and structure are quite different. In this case, we present a novel method for the Vietnamese-Chinese word alignment based on DNN(deep neural network). Firstly, we should convert Vietnamese-Chinese bilingual word into word embedding, and as the input within DNN. Secondly, DNN-HMM word alignment model is constructed by expanding HMM model, which also integrating the context information. The basic model of the experiments are HMM and IBM4. The results of large-scale Vietnamese-Chinese bilingual word alignment task show that this method not only significantly improved its accuracy and recall rate than the two basic models, but also greatly reduced word alignment error rate.

Key words: word alignment, DNN, Vietnamese, Chinese

CLC Number: 

  • TP391
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