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MUSDB18 - a corpus for music separation

MUSDB18 contains 150 full-track songs with stereo mixtures and original sources, split into a training set (100 songs) and a test set (50 songs), for designing and evaluating music source separation algorithms.

AccessFree to access
LicenceLicense statement is still being checked
ProducerZafar Rafii, Antoine Liutkus, Fabian-Robert Stöter, Stylianos Ioannis Mimilakis, Rachel Bittner

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Machine learning & corporaFree to access

Key facts

InstitutionZafar Rafii, Antoine Liutkus, Fabian-Robert Stöter, Stylianos Ioannis Mimilakis, Rachel Bittner
CoverageMusic songs of different styles
Time span2017-12-17 (updated)
Scale150 songs, 1 file (.mp4)

Contents & fields

The dataset contains 150 full-track songs with stereo mixtures and original sources, encoded in Native Instruments stems format (.mp4). Each file contains 5 stereo streams: mixture, drums, bass, other accompaniment, vocals. All signals are stereo, 44.1kHz, AAC @256kbps. Training set: 100 songs; test set: 50 songs.

  • 0 - The mixture——Mixture signal
  • 1 - The drums——Drums signal
  • 2 - The bass——Bass signal
  • 3 - The rest of the accompaniment——Other accompaniment signal
  • 4 - The vocals——Vocals signal

Research uses

Suitable for designing and evaluating music source separation algorithms, e.g., karaoke applications, signal processing research, and as the official dataset for the professionally-produced music recordings task of SiSEC 2018.

Information comes from the source page. Please check that page for current details and terms.

Keywords

music separationsource separationMUSDB18SiSECmultitrack audiodataset

Access and licence

Licence: License statement is still being checked | Free to access

Why this is hard to get on your own

Music source separation research often requires high-quality multitrack datasets, but obtaining well-annotated and clearly licensed music source data is challenging.

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