Error analysis of dialogue act classification

  • Authors:
  • Nick Webb;Mark Hepple;Yorick Wilks

  • Affiliations:
  • Natural Language Processing Group, Department of Computer Science, University of Sheffield, UK;Natural Language Processing Group, Department of Computer Science, University of Sheffield, UK;Natural Language Processing Group, Department of Computer Science, University of Sheffield, UK

  • Venue:
  • TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

We are interested in the area of Dialogue Act (da) tagging. Identifying the dialogue acts of utterances is recognised as an important step towards understanding the content and nature of what speakers say. We have built a simple dialogue act classifier based on purely intra-utterance features – principally word n-gram cue phrases. Although such a classifier performs surprisingly well, rivalling scores obtained using far more sophisticated language modelling techniques for the corpus we address, we want to understand further the issues raised by this approach. We have performed an error analysis of the output of our classifier, with a view to casting light both on the system's performance, and on the da classification scheme itself.