Personalized Smart Music Recommender Therapy Based on Facial Emotion Recognition

Music shows profound impact on publics’ emotions and can be used as a tool for mood regulation. With the growing availability of wearable devices, facial expression recognition technology has become more accessible. This technology can be leveraged to make a personalized music recommendation system based on the one’s sensitive state. This paper examines the neural mechanisms underlying facial expression processing in response to music and compares emotional communication through music with other modalities such as speech. Understanding the intricate relationship between music and facial expression holds promise for enhancing therapeutic interventions, particularly in areas such as emotional expression, communication, and social interaction. In this system, people’s expressions captured by a camera, which are then analyzed to decide the user’s emotional state. The experimental results based; a music recommendation algorithm suggests a playlist that is the most likely to resonate through the user’s current emotional state.