Paper: A Statistical Spoken Dialogue System using Complex User Goals and Value Directed Compression

ACL ID E12-2010
Title A Statistical Spoken Dialogue System using Complex User Goals and Value Directed Compression
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session System Demonstration
Year 2012
Authors

This paper presents the first demonstration of a statistical spoken dialogue system that uses automatic belief compression to rea- son over complex user goal sets. Reasoning over the power set of possible user goals al- lows complex sets of user goals to be rep- resented, which leads to more natural dia- logues. The use of the power set results in a massive expansion in the number of belief states maintained by the Partially Observ- able Markov Decision Process (POMDP) spoken dialogue manager. A modified form of Value Directed Compression (VDC) is applied to the POMDP belief states produc- ing a near-lossless compression which re- duces the number of bases required to rep- resent the belief distribution.