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Decision of the Korean Speech Act using Feature Selection Method  

김경선 (다이퀘스트 연구소)
서정연 (서강대학교 컴퓨터학과)
Publication Information
Journal of KIISE:Software and Applications / v.30, no.3_4, 2003 , pp. 278-284 More about this Journal
Abstract
Speech act is the speaker's intentions indicated through utterances. It is important for understanding natural language dialogues and generating responses. This paper proposes the method of two stage that increases the performance of the korean speech act decision. The first stage is to select features from the part of speech results in sentence and from the context that uses previous speech acts. We use x$^2$ statistics(CHI) for selecting features that have showed high performance in text categorization. The second stage is to determine speech act with selected features and Neural Network. The proposed method shows the possibility of automatic speech act decision using only POS results, makes good performance by using the higher informative features and speed up by decreasing the number of features. We tested the system using our proposed method in Korean dialogue corpus transcribed from recording in real fields, and this corpus consists of 10,285 utterances and 17 speech acts. We trained it with 8,349 utterances and have test it with 1,936 utterances, obtained the correct speech act for 1,709 utterances(88.3%). This result is about 8% higher accuracy than without selecting features.
Keywords
Speech Act Decision; Feature Selection; Neural Network; CHI Statistics;
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