research-article

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

Authors:

Ferdinand Fuhrmann,

Dmitry Bogdanov,

Perfecto HerreraAuthors Info & Claims

AM '10: Proceedings of the 5th Audio Mostly Conference: A Conference on Interaction with Sound

Article No.: 14, Pages 1 - 8

https://doi.org/10.1145/1859799.1859813

Published: 15 September 2010 Publication History

Abstract

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.

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Cited By

Wang JGui TCheng MWu XRuan RDu M(2022)A survey on emotional visualization and visual analysisJournal of Visualization10.1007/s12650-022-00872-526:1(177-198)Online publication date: 10-Sep-2022
https://doi.org/10.1007/s12650-022-00872-5
Okada KKanamaru MTan PKamioka E(2021)Exploiting MUSIC model to solve cold-start user problem in content-based music recommender systemsIntelligent Decision Technologies10.3233/IDT-210196(1-12)Online publication date: 3-Dec-2021
https://doi.org/10.3233/IDT-210196
Khulusi RKusnick JMeinecke CGillmann CFocht JJänicke S(2020)A Survey on Visualizations for Musical DataComputer Graphics Forum10.1111/cgf.1390539:6(82-110)Online publication date: 5-Mar-2020
https://doi.org/10.1111/cgf.13905
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Index Terms

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

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cover image ACM Other conferences

AM '10: Proceedings of the 5th Audio Mostly Conference: A Conference on Interaction with Sound

September 2010

156 pages

ISBN:9781450300469

DOI:10.1145/1859799

Conference Chair:
Katarina Delsing
The Interactive Institute
,
Program Chair:
Mats Liljedahl
The Interactive Institute

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 September 2010

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AM '10: The 5th Audio Mostly Conference

September 15 - 17, 2010

Piteå, Sweden

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Overall Acceptance Rate 177 of 275 submissions, 64%

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Cited By

Wang JGui TCheng MWu XRuan RDu M(2022)A survey on emotional visualization and visual analysisJournal of Visualization10.1007/s12650-022-00872-526:1(177-198)Online publication date: 10-Sep-2022
https://doi.org/10.1007/s12650-022-00872-5
Okada KKanamaru MTan PKamioka E(2021)Exploiting MUSIC model to solve cold-start user problem in content-based music recommender systemsIntelligent Decision Technologies10.3233/IDT-210196(1-12)Online publication date: 3-Dec-2021
https://doi.org/10.3233/IDT-210196
Khulusi RKusnick JMeinecke CGillmann CFocht JJänicke S(2020)A Survey on Visualizations for Musical DataComputer Graphics Forum10.1111/cgf.1390539:6(82-110)Online publication date: 5-Mar-2020
https://doi.org/10.1111/cgf.13905
Bogdanov DHaro MFuhrmann FXambó AGóMez EHerrera P(2019)Semantic audio content-based music recommendation and visualization based on user preference examplesInformation Processing and Management: an International Journal10.1016/j.ipm.2012.06.00449:1(13-33)Online publication date: 22-Nov-2019
https://dl.acm.org/doi/10.1016/j.ipm.2012.06.004
Lehtiniemi AOjala JChisik YGeiger CHasegawa S(2014)Using adaptive avatars for visualizing recent music listening history and supporting music discoveryProceedings of the 11th Conference on Advances in Computer Entertainment Technology10.1145/2663806.2663820(1-10)Online publication date: 11-Nov-2014
https://dl.acm.org/doi/10.1145/2663806.2663820
Gossen TMüller RStober SNürnberger AThomsen BElbæk LIversen OMarkopoulos PGarzotto FDindler C(2014)Search result visualization with characters for childrenProceedings of the 2014 conference on Interaction design and children10.1145/2593968.2593983(125-134)Online publication date: 17-Jun-2014
https://dl.acm.org/doi/10.1145/2593968.2593983
Holm JSiirtola H(2012)A Comparison of Methods for Visualizing Musical GenresProceedings of the 2012 16th International Conference on Information Visualisation10.1109/IV.2012.107(636-645)Online publication date: 11-Jul-2012
https://dl.acm.org/doi/10.1109/IV.2012.107

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