Automatic Clustering of Utterances for a Dialogue Act Design
نویسندگان
چکیده
Automatic clustering of utterances can be useful for the modeling of dialogue acts for dialogue applications. Previously, the Chinese restaurant process (CRP), a non-parametric Bayesian method, has been introduced and has shown promising results for the clustering of utterances in dialogue. This paper introduces the infinite HMM, which is also a non-parametric Bayesian method, and verifies its effectiveness. We also analyze our clustering results to discuss how to derive useful insights for a better dialogue act design.
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