@InProceedings{Supelec16,
author = {Olivier Pietquin and Thierry Dutoit},
title = {{Dynamic Bayesian Networks for NLU Simulation with Application to Dialog Optimal Strategy Learning}},
year = {2006},
booktitle = {{Proceedings of the 31st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}},
volume = {I},
pages = {49-52},
month = {May},
address = {Toulouse (France)},
url = {http://hal-supelec.archives-ouvertes.fr/hal-00216013/fr/},
abstract = {In this paper, we propose to add a model for NLU-related error
generation in a modular environment for computer-based
simulation of man-machine spoken dialogs. This model is jointly
designed with a user model. Both of them are based on the same
underlying Bayesian Network used with different parameters in
such a way that it can generate a consistent user behavior,
according to a goal and the interaction history, and been used
as a concept classifier. The proposed simulation environment
was used to train a reinforcement-learning algorithm on a
simple form-filling task and the results of this experiment
show that the addition of the NLU model helps pointing out
problematic situations that may occur because of
misunderstandings and modifying the dialog strategy accordingly.}
}