Gender and Social Perspective in STEM Training: Artificial Intelligence Systems for Emotion Detection

Keywords: Affective Computing, Smart Sensors, Emotion Detection, Audiovisual, Gender-based Violence.


This paper presents how STEM disciplines and Social Sciences are combined to generate a database of audiovisual stimuli with a gender perspective capable of training an intelligent system for detecting dangerous situations in women who are Victims of Gender Violence. In the methodology of stimulus selection, it has been composed of two procedures: 1) According to research criteria for those related to phylogenetic and associative learning fears; 2) According to criteria based on in-depth interviews with experts in violence and content validation through the technique of expert judges for those related to fears that have to do with traumatic experiences of Gender Violence. The results indicate that the methodological combination improves the selection of audiovisual stimuli that are part of the experiments, better adjusting to the needs of women Victims of Gender violence


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