The audio features of sleep music: Universal and subgroup characteristics
In this groundbreaking study, researchers elucidated the characteristics of music associated with sleep by extracting audio features from a large number of tracks retrieved from sleep playlists at the global streaming platform, Spotify. The study found that, compared to music in general, sleep music tends to be softer, slower, and more often instrumental, without lyrics, and played on acoustic instruments. However, despite these common characteristics, the study also revealed a large amount of variation in sleep music, which clustered into six distinct subgroups.
Interestingly, three of the subgroups included popular tracks that were faster, louder, and more energetic than the average sleep music. These findings shed new light on the audio features of sleep music and highlight the individual variation in the choice of music used for sleep.
Using digital traces, the researchers were able to determine the universal and subgroup characteristics of sleep music in a unique, global dataset, advancing our understanding of how humans use music to regulate their behavior in everyday life. This study provides important insights into the powerful impact of music on sleep, and opens the door to new research into the therapeutic potential of music for promoting healthy sleep patterns.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0278813
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