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http://dx.doi.org/10.3745/KIPSTB.2005.12B.3.365

An analysis of Speech Acts for Korean Using Support Vector Machines  

En Jongmin ((주)하나로 드림)
Lee Songwook (동서대학교 컴퓨터공학과)
Seo Jungyun (서강대학교 컴퓨터학과)
Publication Information
The KIPS Transactions:PartB / v.12B, no.3, 2005 , pp. 365-368 More about this Journal
Abstract
We propose a speech act analysis method for Korean dialogue using Support Vector Machines (SVM). We use a lexical form of a word, its part of speech (POS) tags, and bigrams of POS tags as sentence features and the contexts of the previous utterance as context features. We select informative features by Chi square statistics. After training SVM with the selected features, SVM classifiers determine the speech act of each utterance. In experiment, we acquired overall $90.54\%$ of accuracy with dialogue corpus for hotel reservation domain.
Keywords
Speech Act Analysis; Support Vector Machines; Feature Selection; Machine Learning;
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