Facial Emotion-based Music Recommender System using CNN

Abstract

To find the music as per your emotion is a tedious and time taking task. The music recommendation system has gained a lot of popularity and saves time and energy for the person by playing the right music according to their emotions. Music services make vast volumes of music easily accessible. They are always trying to enhance music organization and search management, addressing the issue of choice, and making it easier to discover new music pieces. Recommendation systems are becoming increasingly common, allowing users to choose acceptable music for any circumstance. However, in terms of emotion-driven suggestions, there is still a gap. Music has a significant impact on humans and is commonly utilized for relaxation, mood control, stress relief, and mental and physical labor. Music therapy may be used in a variety of therapeutic contexts and practices to help people feel better. It is required to construct a suggestion service in addition to looking for expected music objects for customers. The Music Recommendation System (MRS) is designed in this paper to give a personalized music recommendation service using facial emotion-based analysis.