Title :
Using Markov decision process for learning dialogue strategies
Author :
Levin, Esther ; Pieraccini, Roberto ; Eckert, Wieland
Author_Institution :
AT&T Bell Labs., Florham Park, NJ, USA
Abstract :
We introduce a stochastic model for dialogue systems based on Markov decision process. Within this framework we show that the problem of dialogue strategy design can be stated as an optimization problem, and solved by a variety of methods, including the reinforcement learning approach. The advantages of this new paradigm include objective evaluation of dialogue systems and their automatic design and adaptation. We show some preliminary results on learning a dialogue strategy for an air travel information system
Keywords :
Markov processes; decision theory; interactive systems; learning systems; optimisation; speech recognition; traffic information systems; Markov decision process; air travel information system; dialogue systems; interactive system; optimization; reinforcement learning; speech understanding; stochastic model; Computational modeling; Databases; Design optimization; Hidden Markov models; History; Information systems; Learning; Natural languages; Speech recognition; Stochastic systems;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.674402
