Improving Translation Quality by Discarding Most of the Phrasetable

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ConferenceProceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), June 28-30, 2007., Prague, Czech Republic
AbstractIt is possible to reduce the bulk of phrasetables for Statistical Machine translation using a technique based on the significance testing of phrase pair co-occurrence in the parallel corpus. The savings can be quite substantial (up to 90%) and cause no reduction in BLEU score. In some cases, an improvement in BLEU is obtained at the same time although the effect is less pronounced if state-of-the-art phrasetable smoothing is employed.
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AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number49348
NPARC number5763542
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Record identifier2ec0a778-a05e-422b-b9ff-5e1637a2ab8d
Record created2009-03-29
Record modified2016-05-09
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