Dialogue act classification in human-to-human tutorial dialogues

Abstract

We present in this paper preliminary results with dialogue act classification in human-to-human tutorial dialogues. Dialogue acts are ways to characterize the actions of tutors and students based on the language-as-action theory. This work serves our larger goal of identifying patterns of tutors’ actions, in the form of dialogue acts, that relate to learning. The preliminary results we obtained for dialogue act classification using a machine learning approach are promising.