FMA: A Dataset For Music Analysis Data Set
Download: Data Folder, Data Set Description
Spotify is a digital music service that gives you access to millions of songs. Spotify is all the music youâll ever need. Listening is everything - Spotify.
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Spotify is a digital music service that gives you access to millions of songs. Spotify is all the music youâll ever need. Skip to content. Spotify Click the install file to finish up. If your download didn't start, try again. Visit the Microsoft Store to download. Spotify is a digital music service that gives you access to millions of songs. Spotify is all the music youâll ever need. If your download didn't start, try again.
Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson, EPFL LTS2.
Spotify Web API, on the other hand, being an API provided by Spotify itself, allowed us to retrieve for all tracks in MPD and in the Challenge Dataset following features: acousticnes, danceability, energy, instrumentalness, liveness, loudness, speechiness, tempo, valence, popularity. The public part of the dataset consists of roughly 130 million listening sessions with associated user interactions on the Spotify service. In addition to the public part of the dataset, approximately 30.
Data Set 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 ([Web Link])
Attribute 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 ![]()
Relevant Papers:
Spotify Music Dataset
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Kaggle Spotify DatasetSpotify Dataset Download Free
Citation Request:
Spotify Million Playlist Dataset Download
Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. Podcast app for ipad. FMA: A Dataset For Music Analysis. [Web Link], 2017.
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