The MediaEval 2017 AcousticBrainz Genre Task

Content-based Music Genre Recognition from Multiple Sources

Conference paper (2017)

Authors

Dmitry Bogdanov Pompeu Fabra University
Alastair Porter Pompeu Fabra University
Hendrik Schreiber Tagtraum Industries Incorporated
Copyright: © 2017 Dmitry Bogdanov, Alastair Porter, Julián Urbano, Hendrik Schreiber
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Published Date

2017

Language

English

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Abstract

This paper
provides an overview of the AcousticBrainz Genre Task

organized as
part of the MediaEval 2017 Benchmarking Initiative for Multimedia
Evaluation. The task is focused on content-based music genre
recognition using genre annotations from multiple sources and
large-scale music features data available in the AcousticBrainz database.
The goal of our task is to explore how the same music pieces can
be annotated differently by different communities following
different genre taxonomies, and how this should be addressed by
content-based genre recognition systems. We present the task challenges,
the employed ground-truth information and datasets, and the evaluation methodology.


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