Attentive speaking – From listener feedback to interactive adaptation

Dialogue is an interactive and iterative process in which speakers and listeners work towards understanding by jointly coordinating their communicative acts through feedback and adaptation. I will present conceptual and computational models of ‘attentive speaking’ that enable artificial conversational agents (1) to probabilistically reason about, infer, and represent their interlocutors’ listening related mental states (e.g., their degree of understanding); (2) to interactively adapt their language and behaviour such that their interlocutors’ needs, derived from the attributed mental states, are taken into account; and (3) to decide when they need feedback from their interlocutors and how they can elicit it using behavioural cues. I will describe how these models are realised in an incremental behaviour generation architecture for embodied conversational agents, and how the resulting attentive speaker agent is evaluated in a semi-autonomous interaction study.