Machine Translation Method Based on Non-compositional Semantics (Word-Level Sentence-Pattern-Based MT)

Abstract

To overcome the conventional machine translation method, Ikehara et al. proposed a machine translation scheme based on non-compositional semantics. This machine translation scheme requires many sentence patterns which can preserve the semantics of the expression structure. To use this machine translation scheme for Japanese-English machine translation, a compound and complex sentence pattern dictionary, called “ToribankSPD”, have been developed. This dictionary has three levels of sentence patterns: “word-level”, “phrase-level”, and “clause-level”. In this paper, according to the machine translation scheme based on non-compositional semantics, we implemented the Japanese-English sentence-pattern-based machine translation method using the word-level sentence patterns of ToribankSPD. In our experiments, the pattern matching rate was low (about 10 %). However, 72 out of 100 evaluated sentences used the sentence patterns that had an appropriate expression structure, and the translation accuracy of 55 sentences was high.