A bilingual word alignment algorithm of Vietnamese-Chinese based on feature constraint

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 which merges a variety of feature constraint models. In this article, an improved model based on the Vietnamese-Chinese progressive structure and offset features of word sequence is described. From this model which is trained by a log-linear model framework, and with parameters trained by the minimum error rate algorithm, the result of the Vietnamese-Chinese auto-alignment is obtained. The basic model of the experiments is IBM Model 3, and as experimental results suggest, this bilingual word alignment method for Vietnamese and Chinese performs well and precision, recall rates are increased by 28.57 and 25.02 %, AER is reduced by 14.25 %.