research-article

What is this song about anyway?: automatic classification of subject using user interpretations and lyrics

Authors:

Kahyun Choi,

Jin Ha Lee,

J. Stephen DownieAuthors Info & Claims

JCDL '14: Proceedings of the 14th ACM/IEEE-CS Joint Conference on Digital Libraries

Pages 453 - 454

Published: 08 September 2014 Publication History

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Abstract

Metadata research for music digital libraries has traditionally focused on genre. Despite its potential for improving the ability of users to better search and browse music collections, music subject metadata is an unexplored area. The objective of this study is to expand the scope of music metadata research, in particular, by exploring music subject classification based on user interpretations of music. Furthermore, we compare this previously unexplored form of user data to lyrics at subject prediction tasks. In our experiment, we use datasets consisting of 900 songs annotated with user interpretations. To determine the significance of performance differences between the two sources, we applied Friedman's ANOVA test on the classification accuracies. The results show that user-generated interpretations are significantly more useful than lyrics as classification features (p < 0.05). The findings support the possibility of exploiting various existing sources for subject metadata enrichment in music digital libraries.

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[2]

J. S. Downie, "The music information retrieval evaluation exchange (2005-2007): A window into music information retrieval research," Acoustical Science and Technology, vol. 29, no. 4, pp. 247--255, 2008

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X. Hu, J. S. Downie, K. West, and A. F. Ehmann, "Mining music reviews: promising preliminary results," In Proc. of 6th Int. Soc. for Music Inform. Retrieval Conf., London, UK, Sep. 2005, pp. 536--539.

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F. Kleedorfer, P. Knees, and T. Pohle, "Oh Oh Oh Whoah! Towards Automatic Topic Detection in Song Lyrics," In Proc. of 9th Int. Soc. for Music Inform. Retrieval Conf., Philadelphia, PA, Sep. 2008, pp. 287--292.

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J. H. Lee and J. S. Downie, "Survey Of Music Information Needs, Uses, And Seeking Behaviors: Preliminary Findings," In Proc. of 5th Int. Soc. for Music Inform. Retrieval Conf., Barcelona, Spain, Oct. 2004, pp. 441--446.

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Cited By

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Choi KDownie JChen JGonçalves MAllen JFox EKan MPetras V(2018)Exploratory Investigation of Word Embedding in Song Lyric Topic ClassificationProceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries10.1145/3197026.3203883(327-328)Online publication date: 23-May-2018
https://dl.acm.org/doi/10.1145/3197026.3203883
Choi KLee JHu XDownie J(2016)Music subject classification based on lyrics and user interpretationsProceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & Technology10.5555/3017447.3017488(1-10)Online publication date: 14-Oct-2016
https://dl.acm.org/doi/10.5555/3017447.3017488
Choi KLee JWillis CDownie JBogen PAllard SMercer HBeck MCunningham SGoh DHenry G(2015)Topic Modeling Users' Interpretations of Songs to Inform Subject Access in Music Digital LibrariesProceedings of the 15th ACM/IEEE-CS Joint Conference on Digital Libraries10.1145/2756406.2756936(183-186)Online publication date: 21-Jun-2015
https://dl.acm.org/doi/10.1145/2756406.2756936

Index Terms

What is this song about anyway?: automatic classification of subject using user interpretations and lyrics
1. Information systems
  1. Information storage systems
    1. Record storage systems

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Published In

JCDL '14: Proceedings of the 14th ACM/IEEE-CS Joint Conference on Digital Libraries

September 2014

498 pages

ISBN:9781479955695

General Chair:
George Buchanan,
Program Chairs:
Martin Klein,
Andreas Rauber,
Sally Jo Cunningham

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IEEE Press

Publication History

Published: 08 September 2014

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JCDL '14

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JCDL '14: 14th ACM/IEEE-CS Joint Conference on Digital Libraries

September 8 - 12, 2014

London, United Kingdom

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Overall Acceptance Rate 415 of 1,482 submissions, 28%

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December 16 - 20, 2024

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Cited By

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Choi KDownie JChen JGonçalves MAllen JFox EKan MPetras V(2018)Exploratory Investigation of Word Embedding in Song Lyric Topic ClassificationProceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries10.1145/3197026.3203883(327-328)Online publication date: 23-May-2018
https://dl.acm.org/doi/10.1145/3197026.3203883
Choi KLee JHu XDownie J(2016)Music subject classification based on lyrics and user interpretationsProceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & Technology10.5555/3017447.3017488(1-10)Online publication date: 14-Oct-2016
https://dl.acm.org/doi/10.5555/3017447.3017488
Choi KLee JWillis CDownie JBogen PAllard SMercer HBeck MCunningham SGoh DHenry G(2015)Topic Modeling Users' Interpretations of Songs to Inform Subject Access in Music Digital LibrariesProceedings of the 15th ACM/IEEE-CS Joint Conference on Digital Libraries10.1145/2756406.2756936(183-186)Online publication date: 21-Jun-2015
https://dl.acm.org/doi/10.1145/2756406.2756936

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