Phrasetable Smoothing for Statistical Machine Translation

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Conference2006 Conference on Empirical Methods in Natural Language Processing (EMNLP 2006), July 22-23, 2006., Sydney, Australia
AbstractWe discuss different strategies for smoothing the phrasetable in Statistical MT, and give results over a range of translation settings. We show that any type of smoothing is a better idea than the relative-frequency estimates that are often used. The best smoothing techniques yield consistent gains of approximately 1% (absolute) according to the BLEU metric.
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AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48756
NPARC number8914469
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Record identifierf5d2eaa1-babc-4465-8a21-18c4912b1b5c
Record created2009-04-22
Record modified2016-05-09
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