Continuous interaction with a virtual human

Intelligent Virtual Agents

2014

Abstract. Communicative feedback in dialogue is an important mechanism that helps interlocutors coordinate their interaction. Listeners pro-actively provide feedback when they think that it is important for the speaker to know their mental state, and speakers pro-actively seek listener feedback when they need information on whether a listener perceived, understood or accepted their message. This paper presents first steps towards a model for enabling attentive speaker agents to determine when to elicit feedback based on continuous assessment of their information needs about a user's listening state.

Section: Feedback Elicitationmentioning

confidence: 99%

When to Elicit Feedback in Dialogue: Towards a Model Based on the Information Needs of Speakers

Buschmeier

Intelligent Virtual Agents

2014

“…In other work, Reidsma and colleagues [21] have focussed on mechanisms on the level of realisation. Their behaviour realiser 'Elckerlyc' can increase the speech rate and the volume of the speech synthesis flexibly at any point in time.…”

Section: Adapting To the Interlocutor's Needsmentioning

confidence: 99%

Co-constructing Grounded Symbols—Feedback and Incremental Adaptation in Human–Agent Dialogue

Buschmeier

2013

Künstl Intell

Grounding in dialogue concerns the question of how the gap between the individual symbol systems of interlocutors can be bridged so that mutual understanding is possible. This problem is highly relevant to human-agent interaction where mis-or non-understanding is common. We argue that humans minimise this gap by collaboratively and iteratively creating a shared conceptualisation that serves as a basis for negotiating symbol meaning. We then present a computational model that enables an artificial conversational agent to estimate the user's mental state (in terms of contact, perception, understanding, acceptance, agreement and based upon his or her feedback signals) and use this information to incrementally adapt its ongoing communicative actions to the user's needs. These basic abilities are important to reduce friction in the iterative coordination process of co-constructing grounded symbols in dialogue.

“…The mechanisms used for this are based on the handling of graceful interruption in Elckerlyc [17]. In Elckerlyc, this was handled completely in a top-down fashion (see also BML Example 2).…”

Section: Graceful Interruptionmentioning

confidence: 99%

An Incremental Multimodal Realizer for Behavior Co-Articulation and Coordination

Welbergen

Reidsma

Intelligent Virtual Agents

2012

Self Cite

Abstract. Human conversations are highly dynamic, responsive interactions. To enter into flexible interactions with humans, a conversational agent must be capable of fluent incremental behavior generation. New utterance content must be integrated seamlessly with ongoing behavior, requiring dynamic application of co-articulation. The timing and shape of the agent's behavior must be adapted on-the-fly to the interlocutor, resulting in natural interpersonal coordination. We present AsapRealizer, a BML 1.0 behavior realizer that achieves these capabilities by building upon, and extending, two state of the art existing realizers, as the result of a collaboration between two research groups.