Dialogue act recognition under uncertainty using Bayesian networks

Keizer, S. and op den Akker, H.J.A. (2007) Dialogue act recognition under uncertainty using Bayesian networks. Natural Language Engineering, 13 (04). pp. 287-316. ISSN 1351-3249

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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.
Item Type:	Article
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Human Media Interaction (HMI)
Link to this item:	http://purl.utwente.nl/publications/62026
Official URL:	http://dx.doi.org/10.1017/S1351324905004067
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