The Musical Avatar: a visualization of musical preferences by means of audio content description

• Published in: Proceedings of the 5th Audio Mostly Conference on A Conference on Interaction with Sound - AM '10
• Main Authors: Haro Berois, Martín, Xambó, Anna, Fuhrmann, Ferdinand, Bogdanov, Dmitry, Gómez Gutiérrez, Emilia, 1975-, Herrera Boyer, Perfecto, 1964-
• Format: Conference Object
• Language: English
• Published: ACM Association for Computer Machinery
• Subjects: Music information research (MIR); User modeling; Audio content analysis; Semantic retrieval; Music visualization; Piteå
• Online Access: http://hdl.handle.net/10230/47005; https://doi.org/10.1145/1859799.1859813

Comunicació presentada a: AM '10: The 5th Audio Mostly Conference: A Conference on Interaction with Sound celebrat al setembre de 2010 a Piteå, Suècia. The music we like (i.e. our musical preferences) encodes and communicates key information about ourselves. Depicting such preferences in a condensed and easily understandable way is very appealing, especially considering the current trends in social network communication. In this paper we propose a method to automatically generate, given a provided set of preferred music tracks, an iconic representation of a user's musical preferences -- the Musical Avatar. Starting from the raw audio signal we first compute over 60 low-level audio features. Then, by applying pattern recognition methods, we infer a set of semantic descriptors for each track in the collection. Next, we summarize these track-level semantic descriptors, obtaining a user profile. Finally, we map this collection-wise description to the visual domain by creating a humanoid cartoony character that represents the user's musical preferences. We performed a proof-of-concept evaluation of the proposed method on 11 subjects with promising results. The analysis of the users' evaluations shows a clear preference for avatars generated by the proposed semantic descriptors over avatars derived from neutral or randomly generated values. We also found a general agreement on the representativeness of the users' musical preferences via the proposed visualization strategy.