Detection of Dialogue Acts Using Perplexity-Based Word Clustering

  • Iosif Mporas
  • Dimitrios P. Lyras
  • Kyriakos N. Sgarbas
  • Nikos Fakotakis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4629)

Abstract

In the present work we used a word clustering algorithm based on the perplexity criterion, in a Dialogue Act detection framework in order to model the structure of the speech of a user at a dialogue system. Specifically, we constructed an n-gram based model for each target Dialogue Act, computed over the word classes. Then we evaluated the performance of our dialogue system on ten different types of dialogue acts, using an annotated database which contains 1,403,985 unique words. The results were very promising since we achieved about 70% of accuracy using trigram based models.

Keywords

Training Corpus Dialogue System Word Class Word Cluster Linguistic Data Consortium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Iosif Mporas
    • 1
  • Dimitrios P. Lyras
    • 1
  • Kyriakos N. Sgarbas
    • 1
  • Nikos Fakotakis
    • 1
  1. 1.Artificial Intelligence Group, Wire Communications Laboratory, Electrical and Computer Engineering Department, University of Patras, 26500 Rion, PatrasGreece

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