An Analysis of the GTZAN Music Genre Dataset

Bob L. Sturm

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

83 Citations (Scopus)
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Abstract

Most research in automatic music genre recognition
has used the dataset assembled by Tzanetakis et al. in 2001.
The composition and integrity of this dataset,
however, has never been formally analyzed.
For the first time,
we provide an analysis of its composition,
and create a machine-readable index of artist and song titles,
identifying nearly all excerpts.
We also catalog numerous problems with its integrity,
including replications, mislabelings, and distortion.
Original languageEnglish
Title of host publicationProceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies
Volume2012
PublisherAssociation for Computing Machinery
Publication date2012
Pages7-12
ISBN (Print)978-1-4503-1591-3
DOIs
Publication statusPublished - 2012
EventACM Multimedia 2012: Workshop on Music Information Retrieval with User-Centered and Multimodal Strategies - Nara, Japan
Duration: 29 Oct 20122 Nov 2012

Conference

ConferenceACM Multimedia 2012
Country/TerritoryJapan
CityNara
Period29/10/201202/11/2012
SeriesACM Multimedia

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