Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41613
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dc.titleWord sense disambiguation improves statistical machine translation
dc.contributor.authorChan, Y.S.
dc.contributor.authorNg, H.T.
dc.contributor.authorChiang, D.
dc.date.accessioned2013-07-04T08:31:37Z
dc.date.available2013-07-04T08:31:37Z
dc.date.issued2007
dc.identifier.citationChan, Y.S., Ng, H.T., Chiang, D. (2007). Word sense disambiguation improves statistical machine translation. ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics : 33-40. ScholarBank@NUS Repository.
dc.identifier.isbn9781932432862
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41613
dc.description.abstractRecent research presents conflicting evidence on whether word sense disambiguation (WSD) systems can help to improve the performance of statistical machine translation (MT) systems. In this paper, we successfully integrate a state-of-the-art WSD system into a state-of-the-art hierarchical phrase-based MT system, Hiero. We show for the first time that integrating a WSD system improves the performance of a state-of-the-art statistical MT system on an actual translation task. Furthermore, the improvement is statistically significant. © 2007 Association for Computational Linguistics.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTATIONAL SCIENCE
dc.description.sourcetitleACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics
dc.description.page33-40
dc.identifier.isiutNOT_IN_WOS
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