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In spoken dialogue analysis, the speech signal is a rich source of information. We explore in this paper how low level features of the speech signal, such as pitch, loudness, and speaking rate, can inform a model of student interaction in collaborative learning dialogues. For instance, can we observe the way that two people's manners of speaking change over time to model something like rapport? By detecting interaction qualities such as rapport, we can better support collaborative interactions, which have been shown to be highly conducive to learning. For this, we focus on one particular phenomenon of spoken conversation, known as acoustic-prosodic entrainment, where dialogue partners become more similar to each other in their pitch, loudness, or speaking rate during the course of a conversation. We examine whether acoustic-prosodic entrainment is present in a novel corpus of collaborative learning dialogues, how people appear to entrain, to what degree, and report on the acoustic-prosodic features which people entrain on the most. We then investigate whether entrainment can facilitate detection of rapport, a social quality of the interaction. We find that entrainment does correlate to rapport; speakers appear to entrain primarily by matching their prosody on a turn-by-turn basis, and pitch is the most significant acoustic-prosodic feature people entrain on when rapport is present.

Acoustic-Prosodic Entrainment and Rapport in Collaborative Learning Dialogues