Recognising emotions in human and synthetic faces: the role of the upper and lower parts of the face
Proceedings of the 10th international conference on Intelligent user interfaces
Embodied conversational agents on a common ground
From brows to trust
Interpreting Human and Avatar Facial Expressions
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I
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In this paper we present an evaluation study for DaFEx (Database of Facial Expressions), a database created with the purpose of providing a benchmark for the evaluation of the facial expressivity of Embodied Conversational Agents (ECAs). DaFEx consists of 1008 short videos containing emotional facial expressions of the 6 Ekman’s emotions plus the neutral expression. The facial expressions were recorded by 8 professional actors (male and female) in two acting conditions (“utterance” and “non utterance”) and at 3 intensity levels (high, medium, low). The properties of DaFEx were studied by having 80 subjects classify the emotion expressed in the videos. We tested the effect of the intensity level, of the articulatory movements due to speech, and of the actors’ and subjects’ gender, on classification accuracy. We also studied the way error distribute across confusion classes. The results are summarized in this work.