A reliable multidomain model for speech act classification

Authors:
Sangwoo Kang;Harksoo Kim;Jungyun Seo
Affiliations:
Department of Computer Science, Sogang University, South Korea;Program of Computer and Communications Engineering, Kangwon National University, Chuncheon-si, Kangwon-do 200-701, South Korea;Department of Computer Science and Interdisciplinary Program of Integrated Biotechnology, Sogang University, South Korea
Venue:
Pattern Recognition Letters
Year:
2010

Citing 4
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Abstract

In a multidomain dialogue, identifying speech acts is not easy because of the problem of interference between input features. To overcome this problem, we propose a two-step model for speech act classification. In the first step, the proposed model detects a dialogue domain associated with an input utterance. In the second step, the proposed model determines the speech act of the input utterance by using only statistical information about input features in the detected dialogue domain. In the experiment, the precision of the proposed model was higher than that of the baseline system without domain selection by 5.5%. On the basis of this experimental result, we conclude that reducing the interferences between input features by using a domain detection process is effective in improving the precision of speech act classification in multiple domains.