Characterizing music for sleep: A comparison of Spotify playlists

Abstract

There is widespread interest in the use of music to help with sleep, although there is little clear understanding of the features that distinguish music for sleep from music for other purposes. We asked if music intended to facilitate sleep is distinct from music more generally considered as relaxing by comparing the features of tracks comprising three types of playlist on the music streaming service Spotify. Ninety playlists to facilitate sleep, relaxation and, for comparison, energy were gathered, based on titles and descriptions. Our analysis found significant differences between many of the features of the tracks in the three playlist categories, and nature sounds were prominent in sleep music playlists. A nonlinear classification model correctly classified music from sleep playlists with an accuracy rate of 72%, with brightness being the strongest predictor in distinguishing music from sleep and relaxing playlists. Music from sleep playlists could generally be described as acoustic, instrumental, slower, quieter, and with less energy compared to the other playlists, conforming with previous work. Our results emphasize the importance of timbral qualities in music for sleep and confirm sleep music to be distinct from music for relaxation. The results can be used to guide the selection of music for sleep, and the transition from relaxation to sleep.