Bilingual Sense Similarity for Statistical Machine Translation
Boxing Chen, George Foster, Roland Kühn · NPARC · 2010
This paper proposes new algorithms to com-pute the sense similarity between two units (words, phrases, rules, etc.) from parallel cor-pora. The sense similarity scores are computed by using the vector space model. We then ap-ply the algorithms to statistical machine trans-lation by computing the sense similarity be-tween the source and target side of translation rule pairs. Similarity scores are used as addi-tional features of the translation model to im-prove translation performance. Significant im-provements are obtained over a state-of-the-art hierarchical phrase-based machine translation system. 1