Emotional Detection and Music Recommendation System based on User Facial Expression

Abstract

It is often confusing for a person to decide which music he/she have to listen from a massive collection of existing options. There have been several suggestion frameworks available for issues like music, dining, and shopping depending upon the mood of user. The main objective of our music recommendation system is to provide suggestions to the users that fit the user’s preferences. The analysis of the facial expression/user emotion may lead to understanding the current emotional or mental state of the user. Music and videos are one region where there is a significant chance to prescribe abundant choices to clients in light of their inclinations and also recorded information. It is well known that humans make use of facial expressions to express more clearly what they want to say and the context in which they meant their words. More than 60 percent of the users believe that at a certain point of time the number of songs present in their songs library is so large that they are unable to figure out the song which they have to play. By developing a recommendation system, it could assist a user to make a decision regarding which music one should listen to helping the user to reduce his/her stress levels. The user would not have to waste any time in searching or to look up for songs and the best track matching the user’s mood is detected, and songs would be shown to the user according to his/her mood. The image of the user is captured with the help of a webcam. The user’s picture is taken and then as per the mood/emotion of the user an appropriate song from the playlist of the user is shown matching the user’s requirement.