|
Title:
|
The MTG-Jamendo dataset for automatic music tagging
|
|
Author:
|
Bogdanov, Dmitry; Won, Minz; Tovstogan, Philip; Porter, Alastair; Serra, Xavier
|
|
Abstract:
|
Comunicació presentada a: ML4MD Machine Learning for Music Discovery Workshop del congrés ICML2019 celebrat el 15 de juny de 2019 a Long Beach, California. |
|
Abstract:
|
We present the MTG-Jamendo Dataset, a new
open dataset for music auto-tagging. It is built
using music available at Jamendo under Creative
Commons licenses and tags provided by content
uploaders. The dataset contains over 55,000 full
audio tracks with 195 tags from genre, instrument, and mood/theme categories. We provide
elaborated data splits for researchers and report
the performance of a simple baseline approach
on five different sets of tags: genre, instrument,
mood/theme, top-50, and overall. |
|
Abstract:
|
This work was funded by the predoctoral grant MDM-2015-
0502-17-2 from the Spanish Ministry of Economy and Competitiveness linked to the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).
This project has received funding from the European
Union’s Horizon 2020 research and innovation programme
under the Marie Skłodowska-Curie grant agreement No.
765068.
This work has received funding from the European Union’s
Horizon 2020 research and innovation programme under
grant agreement No 688382 “AudioCommons”. |
|
Rights:
|
Aquest document està subjecte a una llicència Creative Commons
https://creativecommons.org/licenses/by/3.0/es/
|
|
Document type:
|
Conference Object
Article - Accepted version |
|
Share:
|
|
