Dialogue act recognition under uncertainty using Bayesian networks

S. Keizer, Hendrikus J.A. op den Akker

    Research output: Contribution to journalArticleAcademicpeer-review

    10 Citations (Scopus)


    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.
    Original languageUndefined
    Article number10.1017/S1351324905004067
    Pages (from-to)287-316
    Number of pages29
    JournalNatural language engineering
    Issue number07ex1846/04
    Publication statusPublished - Dec 2007


    • EWI-11442
    • IR-62026
    • METIS-245792

    Cite this