Rapport has been identified as an important function of human interaction, but to our knowledge no model exists of building and maintaining rapport between humans and conversational agents over the long-term that operates at the level of the dyad. In this paper we leverage existing literature and a corpus of peer tutoring data to develop a framework able to explain how humans in dyadic interactions build, maintain, and destroy rapport through the use of specific conversational strategies that function to fulfill specific social goals, and that are instantiated in particular verbal and nonverbal behaviors. We demonstrate its functionality using examples from our experimental data. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Zhao, R., Papangelis, A., & Cassell, J. (2014). Towards a dyadic computational model of rapport management for human-virtual agent interaction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8637 LNAI, pp. 514–527). Springer Verlag. https://doi.org/10.1007/978-3-319-09767-1_62
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