EmoRec is an innovative Emotion recognition project leveraging advanced Speech processing techniques to analyse speech data and accurately identify the emotional states of individuals. The primary goal of EmoRec is to detect emotional challenges faced by learners and provide Tailored solutions to improve their mood and motivation. By employing state-of-the-art algorithms in Speech analysis and Emotion classification, EmoRec contributes to a Personalized learning experience. The system evaluates the emotional content of spoken expressions, considering factors such as tone, pitch, and speech patterns. Once the emotional state is determined, EmoRec offers specific tasks and recommendations designed to uplift the individual's mood and address the identified difficulties. These recommendations are carefully curated to cater to the unique emotional needs of the learner, fostering a Ee and conducive learning environment. EmoRec's approach is grounded in the understanding that emotional states significantly impact the learning process. By proactively addressing emotional challenges and providing targeted interventions, EmoRec strives to enhance the overall learning experience and contribute to the Emotional well-being of the users.
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Sarala et al. (2024) studied this question.
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