The Free Music Archive (FMA) is a large-scale dataset for evaluating several tasks in Music Information Retrieval. It consists of 343 days of 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.
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MedleyDB, is a dataset of annotated, royalty-free multitrack recordings. It was curated primarily to support research on melody extraction. For each song melody f₀ annotations are provided as well as instrument activations for evaluating automatic instrument recognition. The original dataset consists of 122 multitrack songs out of which 108 include melody annotations.
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GuitarSet is a dataset of high-quality guitar recordings and rich annotations. It contains 360 excerpts 30 seconds in length. The 360 excerpts are the result of the following combinations:
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The iKala dataset is a singing voice separation dataset that comprises of 252 30-second excerpts sampled from 206 iKala songs (plus 100 hidden excerpts reserved for MIREX data mining contest). The music accompaniment and the singing voice are recorded at the left and right channels respectively. Additionally, the human-labeled pitch contours and timestamped lyrics are provided.
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OpenMIC-2018 is an instrument recognition dataset containing 20,000 examples of Creative Commons-licensed music available on the Free Music Archive. Each example is a 10-second excerpt which has been partially labeled for the presence or absence of 20 instrument classes by annotators on a crowd-sourcing platform.
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The Spotify Music Streaming Sessions Dataset (MSSD) consists of 160 million streaming sessions with associated user interactions, audio features and metadata describing the tracks streamed during the sessions, and snapshots of the playlists listened to during the sessions.
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The Bach Doodle Dataset is composed of 21.6 million harmonizations submitted from the Bach Doodle. The dataset contains both metadata about the composition (such as the country of origin and feedback), as well as a MIDI of the user-entered melody and a MIDI of the generated harmonization. The dataset contains about 6 years of user entered music.
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GoodSounds dataset contains around 28 hours of recordings of single notes and scales played by 15 different professional musicians, all of them holding a music degree and having some expertise in teaching. 12 different instruments (flute, cello, clarinet, trumpet, violin, alto sax alto, tenor sax, baritone sax, soprano sax, oboe, piccolo and bass) were recorded using one or up to 4 different microphones. For all the instruments the whole set of playable semitones in the instrument is recorded several times with different tonal characteristics. Each note is recorded into a separate monophonic audio file of 48kHz and 32 bits. Rich annotations of the recordings are available, including details on recording environment and rating on tonal qualities of the sound (“good-sound”, “bad”, “scale-good”, “scale-bad”).
MuMu is a new dataset of more than 31k albums classified into 250 genre classes.
COSIAN is an annotation collection of Japanese popular (J-POP) songs, focusing on singing style and expression of famous solo-singers.
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MedleyDB 2.0 is a superset of the MedleyDB – a dataset of annotated, royalty-free multitrack recordings. The second iteration of the dataset includes 74 new multitrack recordings resulting in 194 songs in total.
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