Exploiting shared Chinese characters in Chinese word segmentation optimization for Chinese-Japanese Machine Translation

Unknown words and word segmentation granularity are two main problems in Chinese word segmentation for Chinese-Japanese Machine Translation (MT). In this paper, we propose an approach of exploiting common Chinese characters shared between Chinese and Japanese in Chinese word segmentation optimization for MT aiming to solve these problems. We augment the system dictionary of a Chinese segmenter by extracting Chinese lexicons from a parallel training corpus. In addition, we adjust the granularity of the training data for the Chinese segmenter to that of Japanese. Experimental results of Chinese-Japanese MT on a phrase-based SMT system show that our approach improves MT performance significantly.