Application of Affective Computing in the Analysis of Emotions of Educational Content for the Prevention of COVID-19

摘要

Affective computing is an emerging research area focused on the development of devices and systems that have the ability to recognize, interpret, process and simulate human emotions in order to improve a user's experience when interacting with a software system. One of the possible fields of application of the techniques provided by affective computing is in the design and generation of multimedia content in the context of formal and non-formal education, which can generate greater interest in students through the transmission of different emotions throughout this content. Based on the above, in this article, an analysis of emotions is carried out on a set of content provided by the Ministry of Health of Colombia as a measure for the prevention and mitigation of contagion by COVID-19. For the development of the study, a tool has been built in the Java language, which allows the segmentation of the audio fragments of the multimedia content, as well as the extraction of the acoustic parameters of arousal and valence, and the application of clustering models on the set of properties extracted from the segments.