Dialogue act recognition under uncertainty using Bayesian networks


Keizer, S. and Akker, H.J.A. op den (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
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/62026
Official URL:https://doi.org/10.1017/S1351324905004067
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