Datasets:
metadata
license: cc
size_categories:
- 10K<n<100K
task_categories:
- audio-to-audio
- audio-classification
pretty_name: Free Music Archive - Medium
dataset_info:
- config_name: default
features:
- name: audio
dtype: audio
- name: title
dtype: string
- name: url
dtype: string
- name: artist
dtype: string
- name: composer
dtype: string
- name: lyricist
dtype: string
- name: publisher
dtype: string
- name: genres
sequence:
class_label:
names:
'0': 20th Century Classical
'1': Abstract Hip-Hop
'2': African
'3': Afrobeat
'4': Alternative Hip-Hop
'5': Ambient
'6': Ambient Electronic
'7': Americana
'8': Asia-Far East
'9': Audio Collage
'10': Avant-Garde
'11': Balkan
'12': Banter
'13': Be-Bop
'14': Big Band/Swing
'15': Bigbeat
'16': Black-Metal
'17': Bluegrass
'18': Blues
'19': Bollywood
'20': Brazilian
'21': Breakbeat
'22': Breakcore - Hard
'23': British Folk
'24': Celtic
'25': Chamber Music
'26': Chill-out
'27': Chip Music
'28': Chiptune
'29': Choral Music
'30': Christmas
'31': Classical
'32': Comedy
'33': Compilation
'34': Composed Music
'35': Contemporary Classical
'36': Country
'37': Country & Western
'38': Cumbia
'39': Dance
'40': Death-Metal
'41': Deep Funk
'42': Disco
'43': Downtempo
'44': Drone
'45': Drum & Bass
'46': Dubstep
'47': Easy Listening
'48': 'Easy Listening: Vocal'
'49': Electro-Punk
'50': Electroacoustic
'51': Electronic
'52': Europe
'53': Experimental
'54': Experimental Pop
'55': Fado
'56': Field Recordings
'57': Flamenco
'58': Folk
'59': Freak-Folk
'60': Free-Folk
'61': Free-Jazz
'62': French
'63': Funk
'64': Garage
'65': Glitch
'66': Gospel
'67': Goth
'68': Grindcore
'69': Hardcore
'70': Hip-Hop
'71': Hip-Hop Beats
'72': Holiday
'73': House
'74': IDM
'75': Improv
'76': Indian
'77': Indie-Rock
'78': Industrial
'79': Instrumental
'80': International
'81': Interview
'82': Jazz
'83': 'Jazz: Out'
'84': 'Jazz: Vocal'
'85': Jungle
'86': Kid-Friendly
'87': Klezmer
'88': Krautrock
'89': Latin
'90': Latin America
'91': Lo-Fi
'92': Loud-Rock
'93': Lounge
'94': Metal
'95': Middle East
'96': Minimal Electronic
'97': Minimalism
'98': Modern Jazz
'99': Musical Theater
'100': Musique Concrete
'101': N. Indian Traditional
'102': Nerdcore
'103': New Age
'104': New Wave
'105': No Wave
'106': Noise
'107': Noise-Rock
'108': North African
'109': Novelty
'110': Nu-Jazz
'111': Old-Time / Historic
'112': Opera
'113': Pacific
'114': Poetry
'115': Polka
'116': Pop
'117': Post-Punk
'118': Post-Rock
'119': Power-Pop
'120': Progressive
'121': Psych-Folk
'122': Psych-Rock
'123': Punk
'124': Radio
'125': Radio Art
'126': Radio Theater
'127': Rap
'128': Reggae - Dancehall
'129': Reggae - Dub
'130': Rock
'131': Rock Opera
'132': Rockabilly
'133': Romany (Gypsy)
'134': Salsa
'135': Shoegaze
'136': Singer-Songwriter
'137': Skweee
'138': Sludge
'139': Soul-RnB
'140': Sound Art
'141': Sound Collage
'142': Sound Effects
'143': Sound Poetry
'144': Soundtrack
'145': South Indian Traditional
'146': Space-Rock
'147': Spanish
'148': Spoken
'149': Spoken Weird
'150': Spoken Word
'151': Surf
'152': Symphony
'153': Synth Pop
'154': Talk Radio
'155': Tango
'156': Techno
'157': Thrash
'158': Trip-Hop
'159': Turkish
'160': Unclassifiable
'161': Western Swing
'162': Wonky
'163': hiphop
- name: tags
sequence: string
- name: released
dtype: timestamp[s]
- name: language
dtype: string
- name: listens
dtype: uint64
- name: artist_url
dtype: string
- name: artist_website
dtype: string
- name: album_title
dtype: string
- name: album_url
dtype: string
- name: license
dtype:
class_label:
names:
'0': CC-BY 1.0
'1': CC-BY 2.0
'2': CC-BY 2.5
'3': CC-BY 3.0
'4': CC-BY 4.0
'5': CC-BY-NC 2.0
'6': CC-BY-NC 2.1
'7': CC-BY-NC 2.5
'8': CC-BY-NC 3.0
'9': CC-BY-NC 4.0
'10': CC-BY-NC-ND 2.0
'11': CC-BY-NC-ND 2.1
'12': CC-BY-NC-ND 2.5
'13': CC-BY-NC-ND 3.0
'14': CC-BY-NC-ND 4.0
'15': CC-BY-NC-SA 2.0
'16': CC-BY-NC-SA 2.1
'17': CC-BY-NC-SA 2.5
'18': CC-BY-NC-SA 3.0
'19': CC-BY-NC-SA 4.0
'20': CC-BY-ND 2.0
'21': CC-BY-ND 2.5
'22': CC-BY-ND 3.0
'23': CC-BY-ND 4.0
'24': CC-BY-SA 2.0
'25': CC-BY-SA 2.5
'26': CC-BY-SA 3.0
'27': CC-BY-SA 4.0
'28': CC-NC-Sampling+ 1.0
'29': CC-Sampling+ 1.0
'30': CC0 1.0
'31': FMA Sound Recording Common Law
'32': Free Art License
'33': Free Music Philosophy (FMP)
- name: copyright
dtype: string
- name: explicit
dtype:
class_label:
names:
'0': 'No'
'1': 'Yes'
- name: instrumental
dtype:
class_label:
names:
'0': 'No'
'1': 'Yes'
- name: allow_commercial_use
dtype:
class_label:
names:
'0': 'No'
'1': 'Yes'
- name: allow_derivatives
dtype:
class_label:
names:
'0': 'No'
'1': 'Yes'
- name: require_attribution
dtype:
class_label:
names:
'0': 'No'
'1': 'Yes'
- name: require_share_alike
dtype:
class_label:
names:
'0': 'No'
'1': 'Yes'
splits:
- name: train
num_bytes: 21944800396.556
num_examples: 24801
download_size: 24013117758
dataset_size: 21944800396.556
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- fma
- free-music-archive
FMA: A Dataset for Music Analysis
Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson.
International Society for Music Information Retrieval Conference (ISMIR), 2017.
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.
Paper: arXiv:1612.01840 - latex and reviews
Slides: doi:10.5281/zenodo.1066119
Poster: doi:10.5281/zenodo.1035847
This Pack
This is the medium dataset, comprising a total of 24,801 samples clipped at 30 seconds over 16 unbalanced genres totaling 206.6 hours hours of audio.
Repack Notes
- 20 files were unreadable by
libsndfile / libmpg123, these were removed. - 179 files had licenses that were unclear on whether or not they permitted redistribution, or the full license text was unavailable. These were removed.
License
- The FMA codebase is released under The MIT License.
- The FMA metadata is released under CC-BY 4.0.
- 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.
Please refer to any of the following URLs for additional details.
Total Duration by License
| License | Total Duration (Percentage) |
|---|---|
| CC-BY-NC-SA 3.0 | 64.4 hours (31.20%) |
| CC-BY-NC-ND 3.0 | 55.2 hours (26.70%) |
| CC-BY-NC-ND 4.0 | 26.8 hours (12.96%) |
| CC-BY-NC-SA 4.0 | 13.7 hours (6.65%) |
| CC-BY 4.0 | 9.3 hours (4.50%) |
| CC-BY-NC 3.0 | 7.1 hours (3.42%) |
| CC-BY-NC 4.0 | 6.4 hours (3.11%) |
| CC-BY 3.0 | 4.7 hours (2.28%) |
| CC-BY-SA 3.0 | 3.8 hours (1.84%) |
| FMA Sound Recording Common Law | 3.4 hours (1.62%) |
| CC-BY-SA 4.0 | 3.4 hours (1.62%) |
| CC-BY-NC-SA 2.0 | 2.0 hours (0.97%) |
| CC-BY-NC-ND 2.0 | 1.7 hours (0.83%) |
| CC0 1.0 | 58.0 minutes (0.47%) |
| CC-BY-ND 3.0 | 51.4 minutes (0.42%) |
| CC-BY-ND 4.0 | 46.4 minutes (0.37%) |
| CC-BY-NC-ND 2.5 | 37.4 minutes (0.30%) |
| CC-BY-NC-SA 2.5 | 34.5 minutes (0.28%) |
| CC-BY-NC 2.5 | 18.5 minutes (0.15%) |
| CC-BY-NC 2.1 | 7.5 minutes(0.06%) |
| CC-NC-Sampling+ 1.0 | 6.0 minutes (0.05%) |
| CC-BY-NC-ND 2.1 | 4.5 minutes (0.04%) |
| CC-BY-SA 2.0 | 4.5 minutes (0.04%) |
| CC-BY-ND 2.0 | 3.5 minutes (0.03%) |
| CC-BY-ND 2.5 | 3.0 minutes (0.02%) |
| Free Art License | 3.0 minutes (0.02%) |
| CC-Sampling+ 1.0 | 2.5 minutes (0.02%) |
| CC-BY 2.0 | 2.0 minutes (0.02%) |
| CC-BY 2.5 | 1.0 minutes (0.01%) |
Citations
@inproceedings{fma_dataset,
title = {{FMA}: A Dataset for Music Analysis},
author = {Defferrard, Micha\"el and Benzi, Kirell and Vandergheynst, Pierre and Bresson, Xavier},
booktitle = {18th International Society for Music Information Retrieval Conference (ISMIR)},
year = {2017},
archiveprefix = {arXiv},
eprint = {1612.01840},
url = {https://arxiv.org/abs/1612.01840},
}
@inproceedings{fma_challenge,
title = {Learning to Recognize Musical Genre from Audio},
subtitle = {Challenge Overview},
author = {Defferrard, Micha\"el and Mohanty, Sharada P. and Carroll, Sean F. and Salath\'e, Marcel},
booktitle = {The 2018 Web Conference Companion},
year = {2018},
publisher = {ACM Press},
isbn = {9781450356404},
doi = {10.1145/3184558.3192310},
archiveprefix = {arXiv},
eprint = {1803.05337},
url = {https://arxiv.org/abs/1803.05337},
}