Paper Contents
Abstract
To listen to music is the favorite pastime of many people, each of who have their own preferred type of music. Users always face the problem of searching through their folders to find the right music to fit their mood, and to make a list of their favorite songs. The facial expressions project attempts to help form a mechanized and automated system for personalizing music to a users emotional state. To help aid this goal, this project provides the framework for gathering songs and the users emotional state at the same time so the songs for each orchestrated emotion can be precisely generated later. A webcam captures facial expressions which are processed by a learning algorithm capable of inferring the most likely emotion corresponding to the detected facial expression. The already known expression is then identified and a corresponding playlist is created in advance style. The created playlist gets read by Spotify API and thus saves user time to search for songs that are most often selected for a particular mood. When selecting the required songs, the API sorts them according to the mood-denoting emotion of joy, sadness, anger or neutral which is detected Spark API.
Copyright
Copyright © 2025 Kalle Sravani. This is an open access article distributed under the Creative Commons Attribution License.
