Student Speech Act Classification Using Machine Learning
Rasor, Travis (University of Memphis) | Olney, Andrew ( University of Memphis ) | D' ( University of Memphis ) | Mello, Sidney
Dialogue-based intelligent tutoring systems use speech act classifiers to categorize student input into answers, questions, and other speech acts. Previous work has primarily focused on question classification. In this paper, we present a complimentary speech act classifier that focuses primarily on non-questions, which was developed using machine learning techniques. Our results show that an effective speech act classifier can be developed directly from labeled data using decision trees.
May-18-2011
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