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 presented an approach using Hidden Markov Models (HMMs) to model the SDS as a process evolving over time.
Modeling User Satisfaction with Hidden Markov Models
Proceedings of the SIGDIAL 2009 Conference
Computer Science