Using Information State to Improve Dialogue Move Identification in a Spoken Dialogue System

In this paper we investigate how to improve the performance of a dialogue move and parameter tagger for a taskoriented dialogue system using the information-state approach. We use a corpus of utterances and information states from an implemented system to train and evaluate a tagger, and then evaluate the tagger in an on-line system. Use of information state context is shown to improve performance of the system. Index Terms: spoken dialogue systems, dialogue management, taggin