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Dialogue act recognition under uncertainty using Bayesian networks

Published online by Cambridge University Press:  01 December 2007

SIMON KEIZER  and
RIEKS OP DEN AKKER
SIMON KEIZER
Affiliation:
Computational Linguistics & Artificial Intelligence Group, Faculty of Arts, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands email: s.keizer@uvt.nl
RIEKS OP DEN AKKER
Affiliation:
Human Media Interaction Group, Department of Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands email: infrieks@cs.utwente.nl
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Abstract

In this paper we discuss the task of dialogue act recognition as a part of interpreting user utterances in context. To deal with the uncertainty that is inherent in natural language processing in general and dialogue act recognition in particular we use machine learning techniques to train classifiers from corpus data. These classifiers make use of both lexical features of the (Dutch) keyboard-typed utterances in the corpus used, and context features in the form of dialogue acts of previous utterances. In particular, we consider probabilistic models in the form of Bayesian networks to be proposed as a more general framework for dealing with uncertainty in the dialogue modelling process.

Type
Papers
Information
Natural Language Engineering , Volume 13 , Issue 4 , December 2007 , pp. 287 - 316
Copyright
Copyright © Cambridge University Press 2007

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