Dimensional emotion prediction from spontaneous head gestures for interaction with sensitive artificial listeners

Authors:
Hatice Gunes;Maja Pantic
Affiliations:
Department of Computing, Imperial College London, London, UK;Department of Computing, Imperial College London, London, UK
Venue:
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Year:
2010

Citing 6
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Abstract

This paper focuses on dimensional prediction of emotions from spontaneous conversational head gestures. It maps the amount and direction of head motion, and occurrences of head nods and shakes into arousal, expectation, intensity, power and valence level of the observed subject as there has been virtually no research bearing on this topic. Preliminary experiments show that it is possible to automatically predict emotions in terms of these five dimensions (arousal, expectation, intensity, power and valence) from conversational head gestures. Dimensional and continuous emotion prediction from spontaneous head gestures has been integrated in the SEMAINE project [1] that aims to achieve sustained emotionally-colored interaction between a human user and Sensitive Artificial Listeners.