FileCoin hosted Free Music Archive
This website is dedicated to the hosting of the Free Music Archive on the Filecoin network.
We introduce the Free Music Archive (FMA), an open and easily accessible dataset suitable for evaluating several tasks in MIR, a field concerned with browsing, searching, and organizing large music collections. The community's growing interest in feature and end-to-end learning is however restrained by the limited availability of large audio datasets. The FMA aims to overcome this hurdle by providing 917 GiB and 343 days of Creative Commons-licensed audio from 106,574 tracks from 16,341 artists and 14,854 albums, arranged in a hierarchical taxonomy of 161 genres. It provides full-length and high-quality audio, pre-computed features, together with track- and user-level metadata, tags, and free-form text such as biographies. We here describe the dataset and how it was created, propose a train/validation/test split and three subsets, discuss some suitable MIR tasks, and evaluate some baselines for genre recognition.Usage » Search data »
Original research and dataset by;
Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson.
International Society for Music Information Retrieval Conference (ISMIR), 2017.
Original GitHub Repository: github.com/mdeff/fma
Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson.
International Society for Music Information Retrieval Conference (ISMIR), 2017.
Original GitHub Repository: github.com/mdeff/fma
- Paper:
arXiv:1612.01840
(latex and reviews) - Slides:
doi:10.5281/zenodo.1066119
- Poster:
doi:10.5281/zenodo.1035847
All code and information on this site is released under the MIT license.
The metadata is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
We do not hold the copyright on the audio and distribute it under the license chosen by the artist.
The dataset is meant for research purposes.
The metadata is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
We do not hold the copyright on the audio and distribute it under the license chosen by the artist.
The dataset is meant for research purposes.