A Kana-Kanji Translation System for Non-Segmented Input Sentences Based on Syntactic and Semantic Analysis

This paper presents a disambiguation approach for t ransla t ing non-segmented-Kana into Kanji. The method consists of two steps. In the first step, an input sentence is analyzed morphologically and ambiguous morphemes are stored in a network form. In the second step, the best path, which is a string of morphemes, is selected by syntactic and semantic analysis based on case grammar. In order to avoid the combinatorial explosion of possible paths, the following heuristic search method is adopted. First, a path that contains the smallest number of weighted-morphemes is chosen as the quasi-best path by a best-first-search technique. Next, the restricted range of morphemes near the quasi-best path is extracted from the morpheme network to construct preferential paths. An experimental system incorporating large dictionaries has been developed and evaluated. A translat ion accracy of 90.5% was obtained. This can be improved to about 95% by optimizing the dictionaries.