Kirk, R. orcid.org/0000-0001-5499-0271 and Timmers, R. orcid.org/0000-0002-1981-0834 (2025) Characterizing music for sleep: a comparison of Spotify playlists. Musicae Scientiae, 29 (1). pp. 62-88. ISSN 1029-8649
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2024. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | relaxation; music classification; music information retrieval; brightness; nature sounds |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Arts and Humanities (Sheffield) > Department of Music (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council 2686055 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 Oct 2024 14:38 |
Last Modified: | 17 Mar 2025 16:18 |
Status: | Published |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/10298649241269011 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:218170 |
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