Harnessing Emotional Intelligence for Music Curation in Recommendation Systems

Abstract

Abstract- When an individual decides the music he or she wants to listen to from a huge collection of already-existing options, sometimes it might get confusing. Diverse maneuvers have been executed for music, pride and food, and shopping based on user mood available, but there is no centrally managed network for all. The objective behind the technology of our music recommendation system is to give user-fitted recommendations to customers. The facial expression/user emotion analysis may a way to rectify defects in the current emotional or mental status of a user. When it comes to music and videos, this is the one area where there is a considerably large avenue for predictions based on customer tastes and previous records. This is a common thing that you've probably heard: that people often use facial expressions to be more direct about what they are really saying and the situation they are in. More than 60% of users agree with the sentiment that it will at some point become so difficult for them to determine which video they should play because quantity of videos in their library is really huge. Through the modelling of a robot dedicated to making recommendations about music to a user, it can facilitate the decision-making of which music one should be listening to and, thereby, lower the stress levels of the user. The user would not need to spend time on music searching or looking up suitable songs, as the best song paired with the user’s mood status would be successfully detected and immediately recommended to him/her by the application. The picture of the user is delivered through the camera incorporated into it. The picture of the user is taken, and then song is displayed on the screen in accordance with the mood or emotion of the user from their playlist, which matches the needs of the user.