Fast-Syntax-Matching-Based Japanese-Chinese Limited Machine Translation

Limited machine translation (LMT) is an unliterate automatic translation based on bilingual dictionary and sentence bank. This paper addresses the Japanese-Chinese LMT problem, proposes two syntactic hypotheses about Japanese texts, and designs a fast-syntax-matching-based Japanese-Chinese (FSMJC) LMT algorithm. In which, the fast syntax matching function, a modified version of Levenshtein function, can predict an approximate similarity of syntactic patterns between two Japanese sentences by a straightforward calculating of their formal occurrences. The experimental results show that the FSMJC LMT algorithm can obtain desirable effects with greatly reduced time costs, and prove that our two syntactic hypotheses are effective on Japanese texts.