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Automatic Dialogue Act Annotation within Arabic Debates

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Computational Linguistics and Intelligent Text Processing (CICLing 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9041))

Abstract

Dialogue acts play an important role in the identification of argumentative discourse structure in human conversations. In this paper, we propose an automatic dialogue acts annotation method based on supervised learning techniques for Arabic debates programs. The choice of this kind of corpora is justified by its large content of argumentative information. To experiment annotation results, we used a specific annotation scheme relatively reliable for our task with a kappa agreement of 84%. The annotation process was yield using Weka platform algorithms experimenting Naive Bayes, SVM and Decision Trees classifiers. We obtained encouraging results with an average accuracy of 53%.

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Author information

Authors and Affiliations

  1. ANLP Research Group, MIRACL Laboratory, University of Sfax, Sfax, Tunisia

    Samira Ben Dbabis & Lamia Hadrich Belguith

  2. University of Applied Science of West Switzerland HE-Arc Ingénierie, Delémont, Switzerland

    Hatem Ghorbel

  3. Faculty of Letters and Human Sciences, University of Sfax, Sfax, Tunisia

    Mohamed Kallel

Authors
  1. Samira Ben Dbabis
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  2. Hatem Ghorbel
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  3. Lamia Hadrich Belguith
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  4. Mohamed Kallel
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Editor information

Editors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico DF, Mexico

    Alexander Gelbukh

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© 2015 Springer International Publishing Switzerland

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Dbabis, S.B., Ghorbel, H., Belguith, L.H., Kallel, M. (2015). Automatic Dialogue Act Annotation within Arabic Debates. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_35

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  • DOI: https://doi.org/10.1007/978-3-319-18111-0_35

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18110-3

  • Online ISBN: 978-3-319-18111-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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