Weighting the Coefficients in PARADISE Models to Increase Their Generalizability

Authors:
Klaus-Peter Engelbrecht;Christine Kühnel;Sebastian Möller
Affiliations:
Deutsche Telekom Laboratories, TU Berlin, Berlin, Germany 10587;Deutsche Telekom Laboratories, TU Berlin, Berlin, Germany 10587;Deutsche Telekom Laboratories, TU Berlin, Berlin, Germany 10587
Venue:
PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
Year:
2008

Citing 4
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Abstract

For spoken dialog systems, PARADISE [Walker et al. 1997] provides a framework to train a user satisfaction prediction model on given data. The approach weights and sums interaction parameters to predict a satisfaction metric calculated from a questionnaire. In this paper, we try to tackle a major problem of these models, namely their weak generalizability. We show, that the weights associated with interaction parameters in the model change in dependence of the system's major problems by examining correlations under different quantities of understanding errors in the dialogs.