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Contribution for newspaper or weekly magazine . 2012
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An analysis of the GTZAN music genre dataset

descriptionPublicationkeyboard_double_arrow_right Article , Conference object , Contribution for newspaper or weekly magazine 02 Nov 2012 Denmark Publisher:ACMJournal:Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies
Authors: Sturm, Bob L.;

doi: 10.1145/2390848.2390851

An analysis of the GTZAN music genre dataset

Abstract

Most research in automatic music genre recognitionhas 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.

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Denmark
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    		 79
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
79
Top 10%
Top 1%
Top 10%
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