Modeling User Satisfaction with Hidden Markov Models

Klaus-Peter Engelbrecht, Florian Gödde, Felix Hartard, Hamed Ketabdar and Sebastian Möller

SIGDIAL Workshop on Discourse and Dialogue (SIGDIAL 2009)
Queen Mary University of London, September 11-12, 2009

Summary

Models for predicting judgments about the quality of Spoken Dialog Systems have been used as overall evaluation metric or as optimization functions in adaptive systems. We describe a new approach to such models, using Hidden Markov Models (HMMs). The user’s opinion is regarded as a continuous process evolving over time. We present the data collection method and results achieved with the HMM model.