An analysis of the GTZAN music genre dataset

Authors:
Bob L. Sturm
Affiliations:
Aalborg University Copenhagen, Copenhagen, Denmark
Venue:
Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies
Year:
2012

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Abstract

A significant amount of work in automatic music genre recognition has used a dataset whose composition and integrity 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. We also catalog numerous problems with its integrity, such as replications, mislabelings, and distortions.