Using a fuzzy emotion model in computer assisted speech therapy

Abstract

Affective computing - machine’s ability to recognize and simulate human affects - has become a main research field for Human Computer Interaction. This paper deal with emotion recognition within a CBST (Computer Based Speech Therapy System) for preschoolers and young schoolchildren. Identifying the emotions of children with speech disorders during the assisted therapy sessions requires an adaptation of classical recognition techniques. That is why, in our article we focus on finding and testing the best emotion representation model to be used in this narrow field. An experiment that validates our proposed approach and indicates the probabilistic coefficient matrix is also presented. The proposed emotion recognition framework can be seen as a future extension of our CBST - Logomon.