Exploiting Sequential Music Preferences via Optimisation-Based Sequencing
Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
In music information retrieval, we often make assertions about what features of music are important to study, one of which is vocals. While the importance of vocals in music preference is both intuitive and anticipated by psychological theory, we have not found any survey studies that confirm this commonly held assertion. We address two questions: (1) what components of music are most salient to people’s musical taste, and (2) how do vocals rank relative to other components of music, in regards to whether people like or dislike a song. Lastly, we explore the aspects of the voice that listeners find important. Two surveys of Spotify users were conducted. The first gathered open-format responses that were then card-sorted into semantic categories by the team of researchers. The second asked respondents to rank the semantic categories derived from the first survey. Responses indicate that vocals were a salient component in the minds of listeners. Further, vocals ranked high as a self-reported factor for a listener liking or disliking a track, among a statistically significant ranking of musical attributes. In addition, we open several new interesting problem areas that have yet to be explored in MIR.
Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
Thomas McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek
Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai