Partially observable Markov decision processes for spoken dialog systems
Computer Speech and Language
Training a real-world POMDP-based dialogue system
NAACL-HLT-Dialog '07 Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies
Agenda-based user simulation for bootstrapping a POMDP dialogue system
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Demonstration of a POMDP voice dialer
HLT-Demonstrations '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Demo Session
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The Hidden Information State (HIS) Dialogue System is the first trainable and scalable implementation of a spoken dialog system based on the Partially-Observable Markov-Decision-Process (POMDP) model of dialogue. The system responds to n-best output from the speech recogniser, maintains multiple concurrent dialogue state hypotheses, and provides a visual display showing how competing hypotheses are ranked. The demo is a prototype application for the Tourist Information Domain and achieved a task completion rate of over 90% in a recent user study.