CloserMusicDB: A Modern Multipurpose Dataset of High Quality Music

Piekarzewicz, Aleksandra, Sroka, Tomasz, Tym, Aleksander, Modrzejewski, Mateusz

arXiv.org Artificial Intelligence 

In this paper, we introduce CloserMusicDB, a collection of full length studio quality tracks annotated by a team of human experts. We describe the selected qualities of our dataset, along with three example tasks possible to perform using this dataset: hook detection, contextual tagging and artist identification. We conduct baseline experiments and provide initial benchmarks for these tasks.

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