Abstract

This paper explores the relative importance of discourse features, prosodic features and their fusion in robust classification of speech acts. Five different feature selection algorithms were used to select set of features to improve the robustness of the classification. The results showed that the ensemble-based classifiers performed best in the classification of 12 speech acts using subsets of both prosodic and discourse features.

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