FMA: A Dataset For Music Analysis
Donated on 5/23/2017
FMA features 106,574 tracks and includes song title, album, artist, genres; play counts, favorites, comments; description, biography, tags; together with audio (343 days, 917 GiB) and features.
Dataset Characteristics
Multivariate, Time-Series
Subject Area
Computer Science
Associated Tasks
Classification, Clustering
Feature Type
Real
# Instances
106574
# Features
-
Dataset Information
Additional Information
* Audio track (encoded as mp3) of each of the 106,574 tracks. It is on average 10 millions samples per track. * Nine audio features (consisting of 518 attributes) for each of the 106,574 tracks. * Given the metadata, multiple problems can be explored: recommendation, genre recognition, artist identification, year prediction, music annotation, unsupervized categorization. * The dataset is split into four sizes: small, medium, large, full. * Please see the paper and the GitHub repository for more information (https://github.com/mdeff/fma)
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
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0 to 10 of 518
Additional Variable Information
Nine audio features computed across time and summarized with seven statistics (mean, standard deviation, skew, kurtosis, median, minimum, maximum): 1. Chroma, 84 attributes 2. Tonnetz, 42 attributes 3. Mel Frequency Cepstral Coefficient (MFCC), 140 attributes 4. Spectral centroid, 7 attributes 5. Spectral bandwidth, 7 attributes 6. Spectral contrast, 49 attributes 7. Spectral rolloff, 7 attributes 8. Root Mean Square energy, 7 attributes 9. Zero-crossing rate, 7 attributes
Dataset Files
| File | Size |
|---|---|
| fma.txt | 201 Bytes |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset fma_a_dataset_for_music_analysis = fetch_ucirepo(id=386) # data (as pandas dataframes) X = fma_a_dataset_for_music_analysis.data.features y = fma_a_dataset_for_music_analysis.data.targets # metadata print(fma_a_dataset_for_music_analysis.metadata) # variable information print(fma_a_dataset_for_music_analysis.variables)
Defferrard, M., Benzi, K., Vandergheynst, P., & Bresson, X. (2017). FMA: A Dataset For Music Analysis [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5HW28.
Creators
Michal Defferrard
Kirell Benzi
Pierre Vandergheynst
Xavier Bresson
DOI
Notes
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.