Exploration of affect detection using semantic cues in virtual improvisation
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
An NVC emotional model for conversational virtual humans in a 3d chatting environment
AMDO'12 Proceedings of the 7th international conference on Articulated Motion and Deformable Objects
AMDO'12 Proceedings of the 7th international conference on Articulated Motion and Deformable Objects
An interdisciplinary VR-architecture for 3D chatting with non-verbal communication
EGVE - JVRC'11 Proceedings of the 17th Eurographics conference on Virtual Environments & Third Joint Virtual Reality
Contextual and active learning-based affect-sensing from virtual drama improvisation
ACM Transactions on Speech and Language Processing (TSLP)
Affect detection from text-based virtual improvisation and emotional gesture recognition
Advances in Human-Computer Interaction
Affect detection from semantic and metaphorical interpretation of virtual drama
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Multimodal intelligent affect detection with Kinect: extended abstract
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Towards a Semantic-Based Approach for Affect and Metaphor Detection
International Journal of Distance Education Technologies
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The survey by Calvo and D'Mello presents a useful overview of the progress of and issues in affect detection. They focus on emotion theories that are relevant to Affective Computing (AC) and suggest stronger collaborations between disciplines. My contribution emphasizes the importance of these issues for AC. In fact, empirical research strongly suggests that facial, vocal, and bodily expressions, subjective experience, and physiological changes are often not very highly correlated in spontaneous situations. Overestimating this cohesion limits the usefulness of affect detection methods in real-world applications. Other factors, such as social context, knowledge regarding the goals of certain interactions, as well as interindividual differences are critically important factors for improving affect detection. At times, social concepts, such as politeness, might be more conducive to model realistic behavior. Knowledge on affect perception is important to estimate the level of realism required to create satisfying and productive interactions between users and artificial systems. Interdisciplinary joint research between social and biological scientists on the one hand and computer scientists and engineers on the other is necessary to deal with the complexity of affective processes. All disciplines involved have much to gain in the process.