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ACL
2010

Bilingual Sense Similarity for Statistical Machine Translation

9 years 15 days ago
Bilingual Sense Similarity for Statistical Machine Translation
This paper proposes new algorithms to compute the sense similarity between two units (words, phrases, rules, etc.) from parallel corpora. The sense similarity scores are computed by using the vector space model. We then apply the algorithms to statistical machine translation by computing the sense similarity between the source and target side of translation rule pairs. Similarity scores are used as additional features of the translation model to improve translation performance. Significant improvements are obtained over a state-of-the-art hierarchical phrase-based machine translation system.
Boxing Chen, George F. Foster, Roland Kuhn
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACL
Authors Boxing Chen, George F. Foster, Roland Kuhn
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