Analysis System of Speech Acts and Discourse Structures Using Maximum Entropy Model

Won Seug Choi, Jeong-Mi Cho, Jungyun Seo

Abstract: We propose a statistical dialogue analysis model to determine discourse structures as well as speech acts using maximum entropy model. The model can automatically acquire probabilistic discourse knowledge from a discourse tagged corpus to resolve ambiguities. We propose the idea of tagging discourse segment boundaries to represent the structural information of discourse. Using this representation we can effectively combine speech act analysis and discourse structure analysis in one framework.