The MediaEval 2017 AcousticBrainz Genre Task: Content-based Music Genre Recognition from Multiple Sources

Dmitry Bogdanov, Alastair Porter, Julian Urbano Merino, Hendrik Schreiber

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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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.


Original languageEnglish
Title of host publicationWorking Notes Proceedings of the MediaEval 2017 Workshop
EditorsGuillaume Gravier, Benjamin Bischke , Claire-Hélène Demarty, Maia Zaharieva, Michael Riegler, Emmanuel Dellandrea, Dmitry Bogdanov, Richard Sutcliffe, Gareth J.F. Jones, Martha Larson
Pages1-3
Number of pages3
Publication statusPublished - 2017
EventMediaEval 2017: Multimedia Benchmark Workshop - Dublin, Ireland
Duration: 13 Sep 201715 Sep 2017

Publication series

NameCEUR Workshop Proceedings
Volume1984
ISSN (Print)1613-0073

Conference

ConferenceMediaEval 2017
CountryIreland
CityDublin
Period13/09/1715/09/17

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