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.
REF ) modeled user satisfaction as process evolving over time with Hidden Markov Models (HMM).
Modeling User Satisfaction with Hidden Markov Models
Proceedings of the SIGDIAL 2009 Conference
Computer Science