Word Re-Segmentation in Chinese-Vietnamese Machine Translation

Abstract

In isolated languages, such as Chinese and Vietnamese, words are not separated by spaces, and a word may be formed by one or more syllables. Therefore, word segmentation (WS) is usually the first process that is implemented in the machine translation process. WS in the source and target languages is based on different training corpora, and WS approaches may not be the same. Therefore, the WS that results in these two languages are not often homologous, and thus word alignment results in many 1-n and n-1 alignment pairs in statistical machine translation, which degrades the performance of machine translation. In this article, we will adjust the WS for both Chinese and Vietnamese in particular and for isolated language pairs in general and make the word boundary of the two languages more symmetric in order to strengthen 1-1 alignments and enhance machine translation performance. We have tested this method on the Computational Linguistics Center’s corpus, which consists of 35,623 sentence pairs. The experimental results show that our method has significantly improved the performance of machine translation compared to the baseline translation system, WS translation system, and anchor language-based WS translation systems.