Tighter Integration of Rule-based and Statistical MT in Serial System Combination

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TypeArticle
ConferenceThe Proceedings of the 22nd International Conference on Computational Linguistics (COLING 2008), August 18-22, 2008., Manchester, United Kingdom
AbstractRecent papers have described machine translation (MT) based on an automatic post-editing or serial combination strategy whereby the input language is first translated into the target language by a rule-based MT (RBMT) system, then the target language output is automatically post-edited by a phrase-based statistical machine translation (SMT) system. This approach has been shown to improve MT quality over RBMT or SMT alone. In this previous work, there was a very loose coupling between the two systems: the SMT system only had access to the final 1-best translations from RBMT. Furthermore, the previous work involved European language pairs and relatively small training corpora. In this paper, we describe a more tightly integrated serial combination for the Chinese-to-English MT task. We will present experimental evaluation results on the 2008 NIST constrained data track where a significant gain in terms of both automatic and subjective metrics is achieved through the tighter coupling of the two systems.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number50397
NPARC number5764530
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Record identifier7edabde5-a76e-4d79-ad9e-9564f39cc12d
Record created2009-03-29
Record modified2016-05-09
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