Abstract
Music can motivate many daily activities as it can regulate mood, increase productivity and sports performance, and raise spirits. However, we know little about how to recommend songs that are motivational for people given their contexts and activities. As a first step towards dealing with this issue, we adopt a theory-driven approach and operationalize the Brunel Music Rating Inventory (BMRI) to identify motivational qualities of music from the audio signal. When we look at frequently listened songs for 14 common daily activities through the lens of motivational music qualities, we find that they are clustered into three high-level latent activity groups: calm, vibrant, and intense. We show that our BMRI features can accurately classify songs in the three classes, thus enabling tools to select and recommend activity-specific songs from existing music libraries without any input required from user. We present the results of a preliminary user evaluation of our song recommender (called PepMusic) and discuss the implications for recommending songs for daily activities.
Highlights
IntroductionRaises spirits, triggers and regulates emotions, and increases work output [1, 2]
Music captures attention, raises spirits, triggers and regulates emotions, and increases work output [1, 2]
We operationalize the Brunel Music Rating Inventory (BMRI) [14], an instrument to assess the motivational qualities of music in exercise and sport, which we extend to other activities (Sect. 4)
Summary
Raises spirits, triggers and regulates emotions, and increases work output [1, 2]. The music people commonly listen to when seeking motivation for a workout is usually different from the music one needs to delve into relaxation. People curate their activity-specific playlists either by putting together songs they deem appropriate, which might be time consuming or bothersome, or by drawing from existing popular playlists that have been suitably composed for the desired activity, which may lack personalization. While others use audio signals, but they still focus on single activity, for example, recommending songs for running sessions [12]. This motivates the need for ways to recommend songs that are motivational for various activities
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