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Unsupervised Classification of Dialogue Acts using a Dirichlet Process Mixture Model

Abstract:

In recent years Dialogue Acts have become a popular means of modelling the communicative intentions of human and machine utterances in many modern dialogue systems. Many of these systems rely heavily on the availability of dialogue corpora that have been annotated with Dialogue Act labels. The manual annotation of dialogue corpora is both tedious and expensive. Consequently, there is a growing interest in unsupervised systems that are capable of automating the annotation process. This paper i...

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Publisher:
Queen Mary University of London
Host title:
Proceedings of SIGDIAL 2009: the 10th Annual Meeting of the Special Interest Group in Discourse and Dialogue
Publication date:
2009-09-01
UUID:
uuid:d22be03d-5c84-4ae4-843f-7c782bef5c19
Local pid:
cs:3548
Deposit date:
2015-03-31

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