Human Emotion Recognition in Education LearningSoftware

Emotions and facial expressions are continuous, variable entities. Researchers from a variety of disciplines have focused on emotion recognition techniques to better understand how users interact with, use, and benefit from the system. Our goal is to understand and extrapolate the learner’s emotional state throughout a learning interaction. One instance is human emotion recognition in Education learning software, which communicates how well a person understands the concepts and their emotions during the assignment of tasks, reaction to different kinds of topics, etc. Assessing a learner’s emotions can gradually improve their learning experience and update the course materials. It is important to take into account our own limitations in this area because they will only be amplified in a machine learning system designed around them because human facial emotion recognition systems lack an innate understanding of human emotion and rely on our capacity to correctly label expressions. The idea is to create a CNN model to categorize the fundamental emotions and thereafter determine the pupils’ psychological states.