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Everett Miller
Everett Miller

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Throughout history, lullabies have been used to help children sleep, and today, with the increasing accessibility of recorded music, many people report listening to music as a tool to improve sleep. Nevertheless, we know very little about this common human habit. In this study, we elucidated the characteristics of music associated with sleep by extracting audio features from a large number of tracks (N = 225,626) retrieved from sleep playlists at the global streaming platform Spotify. Compared to music in general, we found that sleep music was softer and slower; it was more often instrumental (i.e. without lyrics) and played on acoustic instruments. Yet, a large amount of variation was present in sleep music, which clustered into six distinct subgroups. Strikingly, three of the subgroups included popular tracks that were faster, louder, and more energetic than average sleep music. The findings reveal previously unknown aspects of the audio features of sleep music and highlight the individual variation in the choice of music used for sleep. By using digital traces, we 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 behaviour in everyday life.




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In order to paint a better picture of the music present in the Sleep Playlist Dataset, we reduced the many genres tags that each track is assigned by Spotify to one single genre from the list in Table 2. The most popular genre was sleep, followed by pop, ambient and lo-fi (Table 4). 45,993 tracks had unknown genres and 15,816 tracks were unable to be categorised and corresponded to 789 sub-genres. However, as the most prevalent uncategorised sub-genre only has 817 counts, none of the uncategorised sub-genres would appear in the top 20 genres present in the Sleep Playlist Dataset.


Overall, the results of this study clearly highlight the variation within sleep music, and the need to move beyond genre descriptions towards more specific analyses of the audio features of the music. These results can help inform the choice of music for clinical studies, music therapy or personal use. Previously, some clinical trials have used researcher-selected music [56] while others have given participants a choice among pre-selected playlists [57]. So far, it is not clear to which degree the choice of music has an impact on the effect on sleep [58, 59].


The initial Hardcore playlist will feature a mix of traditional modes with the classic ruleset veterans of the franchise are familiar with, including decreased health that cannot be replenished outside of Stim shots, as well as a limited HUD. 041b061a72


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