In this paper, we present a technique for learning new dialog strategies by using a statistical dialog manager that is trained from a dialog corpus. A dialog simulation technique has been developed to acquire data required to train the dialog model and then explore new dialog strategies. A set of measures has also been defined to evaluate the dialog strategy that is automatically learned. We have applied this technique to explore the space of possible dialog strategies for a dialog system that collects monitored data from patients suffering from diabetes. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Griol, D., McTear, M. F., Callejas, Z., López-Cózar, R., Ábalos, N., & Espejo, G. (2010). A methodology for learning optimal dialog strategies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6231 LNAI, pp. 507–514). https://doi.org/10.1007/978-3-642-15760-8_64
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