Domain Tuning of Bilingual Lexicons for MT
MARYLAND UNIV COLLEGE PARK INST FOR ADVANCED COMPUTER STUDIES
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Our 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 coverageaccuracy 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 IR Ni-style NIT system. Our domain-tuned lexicons brought about an improvement in the Blen 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.