Phrase Translation Model Enhanced with Association based Features

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TypeArticle
Proceedings titleProceedings. MT Summit XII. The twelfth Machine Translation Summit International Association for Machine Translation hosted by the Association for Machine Translation in the Americas
ConferenceMT Summit XII. The twelfth Machine Translation Summit International Association for Machine Translation hosted by the Association for Machine Translation in the Americas, Ottawa, Ontario, August 26-30, 2009
AbstractIn this paper, we propose to enhance the phrase translation model with association measures as new feature functions. These features are estimated on counts of phrase pair co-occurrence and their marginal counts. Four feature functions, namely, Dice coefficient, log-likelihood-ratio, hyper-geometric distribution and link probability are exploited and compared. Experimental results demonstrate that the performance of the phrase translation model can be improved by enhancing it with these association based feature functions. Moreover, we study the correlation between the features to predict the usefulness of a new association feature given the existing features.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); NRC Institute for Information Technology
Peer reviewedYes
NRC number52560
NPARC number16335067
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Record identifier045a4960-f69e-435e-aad3-724fc0693af8
Record created2010-11-10
Record modified2016-05-09
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