In this paper, we present ongoing work to develop a robust and natural turn-taking behavior for a social agent to engage a dynamically changing group in a conversation. We specifically focus on discussing likely interaction scenarios for a social robot and how appropriate conversational behavior could unfold in each situation. Preliminary findings from annotations of more than 9,000 dialogue samples from a related domain are used to help judge the importance of different interaction scenarios. We conclude by outlining important general considerations for designing more robust dialogue systems as well as highlight next steps we are taking in developing our character’s turn-taking behavior.
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