Domain Tuning of Bilingual Lexicons for MT

dc.contributor.authorAyan, Necip Fazilen_US
dc.contributor.authorDorr, Bonnieen_US
dc.contributor.authorKolak, Okanen_US
dc.date.accessioned2004-05-31T23:25:57Z
dc.date.available2004-05-31T23:25:57Z
dc.date.created2003-02en_US
dc.date.issued2003-02-27en_US
dc.description.abstractOur overall objective is to translate a domain-specific document in a foreign language (in this case, Chinese) to English. Using automatically induced domain-specific, comparable documents and language-independent clustering, we apply domain-tuning techniques to a bilingual lexicon for downstream translation of the input document to English. We will describe our domain-tuning technique and demonstrate its effectiveness by comparing our results to manually constructed domain-specific vocabulary. Our coverage/accuracy experiments indicate that domain-tuned lexicons achieve 88% precision and 66% recall. We also ran a Bleu experiment to compare our domain-tuned version to its un-tuned counterpart in an IBM-style MT system. Our domain-tuned lexicons brought about an improvement in the Bleu scores: 9.4% higher than a system trained on a uniformly-weighted dictionary and 275% higher than a system trained on no dictionary at all. UMIACS-TR-2003-19 LAMP-TR-096en_US
dc.format.extent105161 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/1262
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4449en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2003-19en_US
dc.relation.ispartofseriesLAMP-TR-096en_US
dc.titleDomain Tuning of Bilingual Lexicons for MTen_US
dc.typeTechnical Reporten_US

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