Paper: Flexible Guidance Generation Using User Model In Spoken Dialogue Systems

ACL ID P03-1033
Title Flexible Guidance Generation Using User Model In Spoken Dialogue Systems
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003
Authors

We address appropriate user modeling in order to generate cooperative responses to each user in spoken dialogue systems. Un- like previous studies that focus on user’s knowledge or typical kinds of users, the user model we propose is more compre- hensive. Specifically, we set up three di- mensions of user models: skill level to the system, knowledge level on the tar- get domain and the degree of hastiness. Moreover, the models are automatically derived by decision tree learning using real dialogue data collected by the sys- tem. We obtained reasonable classifica- tion accuracy for all dimensions. Dia- logue strategies based on the user model- ing are implemented in Kyoto city bus in- formation system that has been developed at our laboratory. Experimental evalua- tion shows that the coop...