Engineering affective computing: A unifying software architecture

• Published in: 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops pp. 1 - 6
• Main Authors: Clay, A., Couture, N., Nigay, L.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-09-2009
• Subjects: Application software; Computer architecture; Data mining; Emotion recognition; Grounding; Interactive systems; Sensor phenomena and characterization; Signal analysis; Software architecture; Testing
• ISBN: 9781424448005; 142444800X
• ISSN: 2156-8103; 2156-8111
• DOI: 10.1109/ACII.2009.5349541

In the field of affective computing, one of the most exciting motivations is to enable a computer to sense users' emotions. To achieve this goal an interactive application has to incorporate emotional sensitivity. Following an engineering approach, the key point is then to define a unifying software architecture that allows any interactive system to become emotionally sensitive. Most research focus on identifying and validating interpretation systems and/or emotional characteristics from different modalities. However, there is little focus on modeling generic software architecture for emotion recognition. Therefore, we propose an integrative approach and define such a generic software architecture based on the grounding theory of multimodality. We state that emotion recognition should be multimodal and serve as a tool for interaction. As such, we use results on multimodality in interactive applications to propose the emotion branch, a component-based architecture model for emotion recognition systems that integrates itself within general models for interactive systems. The emotion branch unifies existing emotion recognition applications architectures following the usual three-level schema: capturing signals from sensors, extracting and analyzing emotionally-relevant characteristics from the obtained data and interpreting these characteristics into an emotion. We illustrate the feasibility and the advantages of the emotion branch with a test case that we developed for gesture-based emotion recognition.