dc.contributor.author |
Bogdanov, Dmitry |
dc.contributor.author |
Porter, Alastair |
dc.contributor.author |
Urbano, Julián |
dc.contributor.author |
Schreiber, Hendrik |
dc.date.accessioned |
2018-11-13T13:46:05Z |
dc.date.available |
2018-11-13T13:46:05Z |
dc.date.issued |
2018 |
dc.identifier.citation |
Bogdanov D, Porter A, Urbano J, Schreiber H. The MediaEval 2018 AcousticBrainz genre task: Content-based music genre recognition from multiple sources. In: Larson M, Arora P, Demarty CH, Riegler M, Bischke B, Dellandrea E, Lux M, Porter A, Jones GJF. MediaEval 2018 Multimedia Benchmark Workshop Working Notes Proceedings of the MediaEval 2018 Workshop. 2018 Oct 29-31; Sophia Antipolis, France. Aachen: CEUR; 2018. [3] p. |
dc.identifier.uri |
http://hdl.handle.net/10230/35744 |
dc.description |
Comunicació presentada al MediaEval 2018 Workshop celebrat a Sophia Antipolis (França) del 29 al 31 d'octubre de 2018. |
dc.description.abstract |
This paper provides an overview of the AcousticBrainz Genre Task
organized as part of the MediaEval 2018 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. |
dc.description.sponsorship |
We thank all contributors to AcousticBrainz. This research has received
funding from the European Union’s Horizon 2020 research
and innovation programme under grant agreements No 688382
(AudioCommons) and 770376-2 (TROMPA), as well as the Ministry
of Economy and Competitiveness of the Spanish Government (Reference:
TIN2015-69935-P). We also thank tagtraum industries for
providing the Tagtraum genre annotations. |
dc.format.mimetype |
application/pdf |
dc.language.iso |
eng |
dc.publisher |
CEUR Workshop Proceedings |
dc.relation.isreferencedby |
https://multimediaeval.github.io/2018-AcousticBrainz-Genre-Task/data/ |
dc.rights |
Copyright © 2018 the authors. |
dc.title |
The MediaEval 2018 AcousticBrainz genre task: content-based music genre recognition from multiple sources |
dc.type |
info:eu-repo/semantics/conferenceObject |
dc.relation.projectID |
info:eu-repo/grantAgreement/EC/H2020/688382 |
dc.relation.projectID |
info:eu-repo/grantAgreement/EC/H2020/770376 |
dc.relation.projectID |
info:eu-repo/grantAgreement/ES/1PE/TIN2015-69935-P |
dc.rights.accessRights |
info:eu-repo/semantics/openAccess |
dc.type.version |
info:eu-repo/semantics/publishedVersion |