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 language | English |
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| Title of host publication | Working Notes Proceedings of the MediaEval 2017 Workshop |
| Editors | Guillaume Gravier, Benjamin Bischke , Claire-Hélène Demarty, Maia Zaharieva, Michael Riegler, Emmanuel Dellandrea, Dmitry Bogdanov, Richard Sutcliffe, Gareth J.F. Jones, Martha Larson |
| Pages | 1-3 |
| Number of pages | 3 |
| Publication status | Published - 2017 |
| Event | MediaEval 2017: Multimedia Benchmark Workshop - Dublin, Ireland Duration: 13 Sept 2017 → 15 Sept 2017 |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Volume | 1984 |
| ISSN (Print) | 1613-0073 |
Conference
| Conference | MediaEval 2017 |
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| Country/Territory | Ireland |
| City | Dublin |
| Period | 13/09/17 → 15/09/17 |