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The State of the Art Ten Years After a State of the Art: Future Research in Music Information Retrieval
2014
Journal of New Music Research
The GTZAN dataset appears in at least 100 published works, and is the most-used public dataset for evaluation in machine listening research for music genre recognition (MGR). Our recent work, however, shows GTZAN has several faults (repetitions, mislabelings, and distortions), which challenge the interpretability of any result derived using it. In this article, we disprove the claims that all MGR systems are affected in the same ways by these faults, and that the performances of MGR systems in
doi:10.1080/09298215.2014.894533
fatcat:6763djkfs5cybgbehinfvwmp4u