Speech acts tagging system for korean using support vector machines

Authors:
Songwook Lee;Jongmin Eun;Jungyun Seo
Affiliations:
Div. of Computer & Information Engineering, Dongseo University, Busan, South Korea;Dept. of Computer Science and Interdisciplinary Program of Integrated Biotechnology, Seoul, South Korea;Dept. of Computer Science and Interdisciplinary Program of Integrated Biotechnology, Seoul, South Korea
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

We propose a speech-act analysis method for Korean dialogue using Support Vector Machines (SVM). We use a lexical word, its part of speech (POS) tags, and bigrams of POS tags as utterance feature and the contexts of the previous utterance as context feature. We select informative features by χ2 statistic. After training SVMs with the selected features, SVM classifiers determine the speech-act of each utterance. In experiment, we acquired overall 90.5% of accuracy with dialogue corpus for hotel reservation domain.