Spotivibes

Tagging playlist vibes with colors

Conference Paper (2019)
Author(s)

Hiba Abderrazik (Student TU Delft)

Giovan Angela (Student TU Delft)

Hans Brouwer (Student TU Delft)

Henky Janse (Student TU Delft)

Sterre Lutz (Student TU Delft)

Gwennan Smitskamp (Student TU Delft)

S. Manolios (TU Delft - Multimedia Computing)

C.C.S. Liem (TU Delft - Multimedia Computing)

Research Group
Multimedia Computing
Copyright
© 2019 Hiba Abderrazik, Giovan Angela, Hans Brouwer, Henky Janse, Sterre Lutz, Gwennan Smitskamp, S. Manolios, C.C.S. Liem
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Hiba Abderrazik, Giovan Angela, Hans Brouwer, Henky Janse, Sterre Lutz, Gwennan Smitskamp, S. Manolios, C.C.S. Liem
Research Group
Multimedia Computing
Pages (from-to)
55-59
Reuse Rights

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Abstract

Music is often both personally and affectively meaningful to human listeners. However, little work has been done to create music recommender systems that take this into account. In this demo proposal, we present Spotivibes: a first prototype for a new color-based tagging and music recommender system. This innovative tagging system is designed to take the users' personal experience of music into account and allows them to tag their favorite songs in a non-intrusive way, which can be generalized to their entire library. The goal of Spotivibes is twofold: to help users better tag their playlists to get better playlists and to provide research data on implicit grouping mechanisms in personal music collections. The system was tested with a user study on 34 Spotify users.