A methodology for learning optimal dialog strategies

Authors:
David Griol;Michael F. McTear;Zoraida Callejas;Ramón López-Cózar;Nieves Ábalos;Gonzalo Espejo
Affiliations:
Dept. of Computer Science, Carlos III University of Madrid, Spain;School of Computing and Mathematics, University of Ulster, Northern Ireland;Dept. of Languages and Computer Systems, CITIC, University of Granada, Spain;Dept. of Languages and Computer Systems, CITIC, University of Granada, Spain;Dept. of Languages and Computer Systems, CITIC, University of Granada, Spain;Dept. of Languages and Computer Systems, CITIC, University of Granada, Spain
Venue:
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Year:
2010

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Abstract

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.