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Domain Adaptation Method for LHMM-based English Part-of-Speech Tagger  

Kwon, Oh-Woog (한국전자통신연구원 언어처리연구팀)
Kim, Young-Gil (한국전자통신연구원 언어처리연구팀)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.16, no.10, 2010 , pp. 1000-1004 More about this Journal
Abstract
A large number of current language processing systems use a part-of-speech tagger for preprocessing. Most language processing systems required a tagger with the highest possible accuracy. Specially, the use of domain-specific advantages has become a hot issue in machine translation community to improve the translation quality. This paper addresses a method for customizing an HMM or LHMM based English tagger from general domain to specific domain. The proposed method is to semi-automatically customize the output and transition probabilities of HMM or LHMM using domain-specific raw corpus. Through the experiments customizing to Patent domain, our LHMM tagger adapted by the proposed method shows the word tagging accuracy of 98.87% and the sentence tagging accuracy of 78.5%. Also, compared with the general tagger, our tagger improved the word tagging accuracy of 2.24% (ERR: 66.4%) and the sentence tagging accuracy of 41.0% (ERR: 65.6%).
Keywords
part-of-speech tagger; domain adaptation method; LHMM; HMM;
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