The MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sources

dc.contributor.authorBogdanov, Dmitryca
dc.contributor.authorPorter, Alastairca
dc.contributor.authorUrbano, Juliánca
dc.contributor.authorSchreiber, Hendrikca
dc.date.accessioned2017-10-11T17:43:37Z
dc.date.available2017-10-11T17:43:37Z
dc.date.issued2017
dc.descriptionComunicació presentada a: MediaEval2017 Workshop, celebrat del 13 al 15 de setembre de 2017 a Dublin, Irlanda.ca
dc.description.abstractThis 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.en
dc.description.sponsorshipThis research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688382 (AudioCommons).en
dc.format.mimetypeapplication/pdf
dc.identifier.citationBogdanov D, Porter A, Urbano J, Schreiber H. The MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sources. In: Gravier G, Bischke B, Demarty CH, Zaharieva M, Riegler M, Dellandrea E, Bogdanov D, Sutcliffe R, Jones GJF, Larson M. MediaEval2017 Multimedia Benchmark Workshop. Working Notes Proceedings of the MediaEval 2017 Workshop co-located with the Conference and Labs of the Evaluation Forum (CLEF 2017); 2017 Sep 13-15; Dublin, Ireland. Aachen: CEUR; 2017. [3] p.
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/10230/32932
dc.language.isoeng
dc.publisherCEUR Workshop Proceedings
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/688382
dc.rightsCopyright © 2017 the authors.
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordMusic genre recognitionen
dc.subject.keywordMusic information retrievalen
dc.subject.keywordMusic datasetsen
dc.subject.keywordMusic genresen
dc.subject.keywordMusic metadataen
dc.subject.keywordAudio analysisen
dc.subject.keywordMusic classificationen
dc.subject.keywordSound and music computingen
dc.titleThe MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sourcesca
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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