Creating Interactive Virtual Humans: Some Assembly Required
IEEE Intelligent Systems
Contextual recognition of head gestures
ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
Presence: Teleoperators and Virtual Environments
IVA '07 Proceedings of the 7th international conference on Intelligent Virtual Agents
Creating Rapport with Virtual Agents
IVA '07 Proceedings of the 7th international conference on Intelligent Virtual Agents
Learning Smooth, Human-Like Turntaking in Realtime Dialogue
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
Predicting Listener Backchannels: A Probabilistic Multimodal Approach
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
The effect of affective iconic realism on anonymous interactants' self-disclosure
CHI '09 Extended Abstracts on Human Factors in Computing Systems
Learning a model of speaker head nods using gesture corpora
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Expression of Moral Emotions in Cooperating Agents
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Can Virtual Human Build Rapport and Promote Learning?
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Can virtual humans be more engaging than real ones?
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Maintaining reality: Relational agents for antipsychotic medication adherence
Interacting with Computers
Parasocial consensus sampling: combining multiple perspectives to learn virtual human behavior
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
Backchannels: quantity, type and timing matters
IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
Cultural study on speech duration and perception of virtual agent's nodding
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
Timing and entrainment of multimodal backchanneling behavior for an embodied conversational agent
Proceedings of the 15th ACM on International conference on multimodal interaction
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Backchannel feedback is an important kind of nonverbal feedback within face-to-face interaction that signals a person's interest, attention and willingness to keep listening. Learning to predict when to give such feedback is one of the keys to creating natural and realistic virtual humans. Prediction models are traditionally learned from large corpora of annotated face-to-face interactions, but this approach has several limitations. Previously, we proposed a novel data collection method, Parasocial Consensus Sampling, which addresses these limitations. In this paper, we show that data collected in this manner can produce effective learned models. A subjective evaluation shows that the virtual human driven by the resulting probabilistic model significantly outperforms a previously published rule-based agent in terms of rapport, perceived accuracy and naturalness, and it is even better than the virtual human driven by real listeners' behavior in some cases.