The 2018 AcousticBrainz Genre Task: Content-based music genre recognition from multiple sources

Task Description
The goal of our task is to understand how genre classification can explore and address the subjective and culturally-dependent nature of genre categories. Traditionally genre classification is performed using a single source of ground truth with broad genre categories as class labels. In contrast, this task is aimed at exploring how to exploit and combine multiple sources of annotations, each of which are more detailed. Each source has a different genre class space, providing an opportunity to analyze the problem of music genre recognition from new perspectives and with the potential of reducing evaluation bias.

More information, including the schedule, is available on the Github page:
https://multimediaeval.github.io/2018-AcousticBrainz-Genre-Task

Task organizers
Dmitry Bogdanov, Music Technology Group, Universitat Pompeu Fabra, Spain (first.last @upf.edu)
Alastair Porter, Music Technology Group, Universitat Pompeu Fabra, Spain (first.last @upf.edu)
Julián Urbano, Delft University of Technology, Netherlands
Hendrik Schreiber, Tagtraum Industries Incorporated, USA

Acknowledgements
AcousticBrainz and Audio Commons

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This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688382.