Paper: Context Management with Topics for Spoken Dialogue Systems

ACL ID P98-1103
Title Context Management with Topics for Spoken Dialogue Systems
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1998

In this paper we discuss the use of discourse con- text in spoken dialogue systems and argue that the knowledge of the domain, modelled with the help of dialogue topics is important in maintaining robust- ness of the system and improving recognition accu- racy of spoken utterances. We propose a topic model which consists of a domain model, structured into a topic tree, and the Predict-Support algorithm which assigns topics to utterances on the basis of the topic transitions described in the topic tree and the words recognized in the input utterance. The algorithm uses a probabilistic topic type tree and mutual infor- mation between the words and different topic types, and gives recognition accuracy of 78.68% and preci- sion of 74.64%. This makes our topic model highly comparable to discour...