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Combining Domain Adaptation Approaches for Medical Text Translation
Longyue Wang; Yi Lu; Derek F. Wong; Lidia S. Chao; Yiming Wang; Francisco Oliveira
2014
Conference Namethe Ninth Workshop on Statistical Machine Translation
Source PublicationProceedings of the Ninth Workshop on Statistical Machine Translation
Pages254–259
Conference DateJune 26–27, 2014.
Conference PlaceBaltimore, Maryland USA
Abstract

This paper explores a number of simple and effective techniques to adapt statistical machine translation (SMT) systems in the medical domain. Comparative experiments are conducted on large corpora for six language pairs. We not only compare each adapted system with the baseline, but also combine them to further improve the domain-specific systems. Finally, we attend the WMT2014 medical summary sentence translation constrained task and our systems achieve the best BLEU scores for Czech-English, EnglishGerman, French-English language pairs and the second best BLEU scores for reminding pairs.

DOI10.3115/v1/W14-3331
URLView the original
Language英语
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Document TypeConference paper
专题Faculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationNatural Language Processing & Portuguese-Chinese Machine Translation Laboratory, Department of Computer and Information Science, University of Macau, Macau, China
First Author AffilicationUniversity of Macau
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Longyue Wang,Yi Lu,Derek F. Wong,et al. Combining Domain Adaptation Approaches for Medical Text Translation[C],2014:254–259.
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