Automated Affect Recognition

Previous solutions for affect recognition are based on non-representative and unrealistic data sets. The first step towards better emotion recognition is therefore the collection of a balanced video data set in a situation as natural as possible using standardized test procedures. For this purpose, we have developed two paradigms: The Berlin Emotion Recognition Test (BERT) is a computer-based task for sensitively assessing emotion recognition of a person. The Simulated Interaction Task (SIT) is a simulated social interaction that records non-verbal interaction behavior. With this data we develop machine learning algorithms for affect recognition, using innovative fusion approaches to integrate different modalities (voice, facial expression, gaze behavior).

This research is funded by the "Empathische Künstliche Intelligenz" (EKI) grant, FKZ 01IS20046.