Robust Real-Time Face Detection
International Journal of Computer Vision
A possible model for predicting listeners' emotional engagement
CMMR'05 Proceedings of the Third international conference on Computer Music Modeling and Retrieval
Measuring synchrony in dialog transcripts
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
Conversational involvement and synchronous nonverbal behaviour
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
Proceedings of the 15th ACM on International conference on multimodal interaction
Towards developing a model for group involvement and individual engagement
Proceedings of the 15th ACM on International conference on multimodal interaction
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Although an increasing amount of research has been carried out into human-machine interaction in the last century, even today we are not able to fully understand the dynamic changes in human interaction. Only when we achieve this, will we be able to go beyond a one-to-one mapping between text and speech and be able to add social information to speech technologies. Social information is expressed to a high degree through prosodic cues and movement of the body and the face. The aim of this paper is to use those cues to make one aspect of social information more tangible; namely participants' degree of involvement in a conversation. Our results for voice span and intensity, and our preliminary results on the movement of the body and face suggest that these cues are reliable cues for the detection of distinct levels of participants involvement in conversation. This will allow for the development of a statistical model which is able to classify these stages of involvement. Our data indicate that involvement may be a scalar phenomenon.