benjamin-paine
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README.md
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data_files:
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- split: train
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path: data/train-*
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---
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data_files:
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- split: train
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path: data/train-*
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license: cc
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task_categories:
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- audio-to-audio
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- audio-classification
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tags:
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- fma
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- free-music-archive
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pretty_name: Free Music Archive - Large
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---
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# FMA: A Dataset for Music Analysis
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[Michaël Defferrard](https://deff.ch/), [Kirell Benzi](https://kirellbenzi.com/), [Pierre Vandergheynst](https://people.epfl.ch/pierre.vandergheynst), [Xavier Bresson](https://www.ntu.edu.sg/home/xbresson).
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**International Society for Music Information Retrieval Conference (ISMIR), 2017.**
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> 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. Code, data, and usage examples are available at https://github.com/mdeff/fma.
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Paper: [arXiv:1612.01840](https://arxiv.org/abs/1612.01840) - [latex and reviews](https://github.com/mdeff/paper-fma-ismir2017)
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Slides: [doi:10.5281/zenodo.1066119](https://doi.org/10.5281/zenodo.1066119)
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Poster: [doi:10.5281/zenodo.1035847](https://doi.org/10.5281/zenodo.1035847)
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## Repack Notes
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A number (<1%) of files present in the original dataset do not have clear licenses. These were excluded from this dataset.
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# License
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- The [FMA codebase](https://github.com/mdeff/fma) is released under [The MIT License](https://github.com/mdeff/fma/blob/master/LICENSE.txt).
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- The FMA metadata is released under [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0).
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- The individual files are released under various Creative Commons family licenses, with a small amount of additional licenses. **Each file has its license attached and important details of the license enumerated.** To make it easy to use for developers and trainers, a configuration is available to limit only to commercially-usable data.
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Please refer to any of the following URLs for additional details.
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| Class Label | License Name | URL |
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| ----------- | ------------ | --- |
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| 0 | CC-BY 1.0 | https://creativecommons.org/licenses/by/1.0/ |
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| 1 | CC-BY 2.0 | https://creativecommons.org/licenses/by/2.0/ |
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| 2 | CC-BY 2.5 | https://creativecommons.org/licenses/by/2.5/ |
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| 3 | CC-BY 3.0 | https://creativecommons.org/licenses/by/3.0/ |
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| 4 | CC-BY 4.0 | https://creativecommons.org/licenses/by/4.0/ |
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| 5 | CC-BY-NC 2.0 | https://creativecommons.org/licenses/by-nc/2.0/ |
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| 6 | CC-BY-NC 2.1 | https://creativecommons.org/licenses/by-nc/2.1/ |
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| 7 | CC-BY-NC 2.5 | https://creativecommons.org/licenses/by-nc/2.5/ |
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| 8 | CC-BY-NC 3.0 | https://creativecommons.org/licenses/by-nc/3.0/ |
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| 9 | CC-BY-NC 4.0 | https://creativecommons.org/licenses/by-nc/4.0/ |
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| 10 | CC-BY-NC-ND 2.0 | https://creativecommons.org/licenses/by-nc-nd/2.0/ |
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| 11 | CC-BY-NC-ND 2.1 | https://creativecommons.org/licenses/by-nc-nd/2.1/ |
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| 12 | CC-BY-NC-ND 2.5 | https://creativecommons.org/licenses/by-nc-nd/2.5/ |
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| 13 | CC-BY-NC-ND 3.0 | https://creativecommons.org/licenses/by-nc-nd/3.0/ |
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| 14 | CC-BY-NC-ND 4.0 | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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| 15 | CC-BY-NC-SA 2.0 | https://creativecommons.org/licenses/by-nc-sa/2.0/ |
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| 16 | CC-BY-NC-SA 2.1 | https://creativecommons.org/licenses/by-nc-sa/2.1/ |
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| 17 | CC-BY-NC-SA 2.5 | https://creativecommons.org/licenses/by-nc-sa/2.5/ |
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| 18 | CC-BY-NC-SA 3.0 | https://creativecommons.org/licenses/by-nc-sa/3.0/ |
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| 19 | CC-BY-NC-SA 4.0 | https://creativecommons.org/licenses/by-nc-sa/4.0/ |
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| 20 | CC-BY-ND 2.0 | https://creativecommons.org/licenses/by-nd/2.0/ |
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| 21 | CC-BY-ND 2.5 | https://creativecommons.org/licenses/by-nd/2.5/ |
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| 22 | CC-BY-ND 3.0 | https://creativecommons.org/licenses/by-nd/3.0/ |
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| 23 | CC-BY-ND 4.0 | https://creativecommons.org/licenses/by-nd/4.0/ |
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| 24 | CC-BY-SA 2.0 | https://creativecommons.org/licenses/by-sa/2.0/ |
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| 25 | CC-BY-SA 2.5 | https://creativecommons.org/licenses/by-sa/2.5/ |
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| 26 | CC-BY-SA 3.0 | https://creativecommons.org/licenses/by-sa/3.0/ |
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| 27 | CC-BY-SA 4.0 | https://creativecommons.org/licenses/by-sa/4.0/ |
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| 28 | CC-NC-Sampling+ 1.0 | https://creativecommons.org/licenses/nc-sampling+/1.0/ |
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| 29 | CC-Sampling+ 1.0 | https://creativecommons.org/licenses/sampling+/1.0/ |
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| 30 | FMA Sound Recording Common Law | https://freemusicarchive.org/Sound_Recording_Common_Law |
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| 31 | Free Art License | https://artlibre.org/licence/lal/en |
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| 32 | Free Music Philosophy (FMP) | https://irdial.com/free_and_easy.htm |
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# Citations
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```
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@inproceedings{fma_dataset,
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title = {{FMA}: A Dataset for Music Analysis},
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author = {Defferrard, Micha\"el and Benzi, Kirell and Vandergheynst, Pierre and Bresson, Xavier},
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booktitle = {18th International Society for Music Information Retrieval Conference (ISMIR)},
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year = {2017},
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archiveprefix = {arXiv},
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eprint = {1612.01840},
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url = {https://arxiv.org/abs/1612.01840},
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}
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```
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```
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@inproceedings{fma_challenge,
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title = {Learning to Recognize Musical Genre from Audio},
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subtitle = {Challenge Overview},
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author = {Defferrard, Micha\"el and Mohanty, Sharada P. and Carroll, Sean F. and Salath\'e, Marcel},
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booktitle = {The 2018 Web Conference Companion},
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year = {2018},
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publisher = {ACM Press},
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isbn = {9781450356404},
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doi = {10.1145/3184558.3192310},
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archiveprefix = {arXiv},
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eprint = {1803.05337},
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url = {https://arxiv.org/abs/1803.05337},
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}
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```
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