Personalized Music Playlist Generation Method for Placing the Listener in a Positive Mood

Abstract

This study proposes a method for the automatic design of personalized playlists that places a listener in a positive mood (uplifting or relaxing feelings) based on individual’s impressions of audio tracks. This method designs a playlist with gradually changing personal impressions of audio tracks and induces individuals’ moods to be uplifting or relaxing. It estimates the subjective impressions of all audio tracks in the music database using the bagging method, a type of ensemble learning, and creates a personalized playlist. This study investigated the changes in a listener’s mood before and after listening to personalized playlists, non-personalized playlists, and playlists with randomly selected tracks using a psychological scale. Consequently, many personalized playlists have shifted the listener into a positive mood more than non-personalized playlists or random design playlists.