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Published in:
2007 | OriginalPaper | Chapter
Detection of Dialogue Acts Using Perplexity-Based Word Clustering
Authors : Iosif Mporas, Dimitrios P. Lyras, Kyriakos N. Sgarbas, Nikos Fakotakis
Published in: Text, Speech and Dialogue
Publisher: Springer Berlin Heidelberg
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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.