Published May 4, 2022 | Version 1.0.0-multitracks+midi
Dataset Restricted

EnsembleSet

  • 1. Queen Mary University of London

Description

We introduce a novel multitrack dataset called EnsembleSet generated using the Spitfire BBC Symphony Orchestra library and ensemble scores from RWC Classical Music Database and Mutopia. Our data generation method introduces automated articulation mapping for different playing styles based on the input MIDI/MusicXML data. The sample library also enables us to render the dataset with 20 different mix/microphone configurations allowing us to study various recording scenarios for each performance. The dataset presents 80 tracks (6+ hours) with a range of string, wind, and brass instruments arranged as chamber ensembles. The dataset consists a total of 498.5 hours of unique instrument tracks. The paper associated with this dataset can be found here. Code associated to experiments in the paper can be found on github.

Click here for audio examples.

Note: The 1.0.0-multitracks+midi version requires you to sign the pledge for RWC Music Database usage, but the 1.0.0-multitracks version can be downloaded without any restrictions.

Contents:

80 Chamber ensemble pieces rendered from MIDI/MusicXML files using Spitfire BBC Symphony Orchestra Professional Library. MIDI files with keyswitches/articulation maps are included in this version. Each folder contains 20 sub-folders containing 20 unique microphone/mix configurations:

  1. Mono: Mono microphone positioned behind the conductor's head.
  2. Leader: Condenser microphone placed in front of the leader of the section (only for Violins, Violas, Celli and Basses)
  3. Tree: Three omnidirectional microphones placed in the traditional Decca Tree arrangement, stated high above the conductor's head.
  4. Out (Outriggers): Two omnidirectional microphones placed close to the Violin 1 and Cello section parallel to the Decca Tree.
  5. Amb (Ambient): Two omnidirectional microphones placed further off-stage and higher than the Outriggers.
  6. Balcony: Two omnidirectional microphones placed at the back of the room, high up in the balcony.
  7. Stereo: Two Coles 4038 microphones placed in a stereo arrangement behind the conductor at head height.
  8. Mids: A stereo pair placed above the Brass, Woodwind and Percussion sections.
  9. Sides: Two omnidirectional microphones placed on the very edge of the stage, parallel to the Decca Tree and Outriggers.
  10. AtmosF: Two omnidirectional microphones placed high above in front of the stage.
  11. AtmosR: Two omnidirectional microphones placed high above at the back of the room.
  12. Close: The section close microphones for each performer, panned similar to the placement of the performers w.r.t. the conductor.
  13. CloseW: The section close microphones for each performer, panned center.
  14. SpStr (Spill String): Downmix of all the close mics for the string section.
  15. SpBr (Spill Brass): Downmix of all the close mics for the brass section.
  16. SpWW (Spill Woodwind): Downmix of all the close mics for the woodwind section.
  17. SpPer (Spill Percussion): Downmix of all the close mics for the percussion section.
  18. SpFl (Spill Full): Downmix of all the close mics for all sections.
  19. Mix_1: This is specifically a mix of the Decca Tree, Outriggers, Ambient, Balcony, Mids (except for strings), and Close signals.
  20. Mix_2: This is specifically a mix of the Decca Tree, Outriggers, Ambient, Balcony, Sides, Atmos Front, Stereo, Mids and Close signals with some added Compression, EQ and Reverb.

Licensing:

The dataset utilizes 9 MIDI tracks from the RWC Classical Music Database (Track names: RM-Cxxx) for which the copyrights belong to the National Institute of Advanced Industrial Science and Technology and are managed by the RWC Music Database Administrator. Users may freely use this data for research purposes without facing the usual copyright restrictions as long as they fulfill the requirements as mentioned here. The remaining 71 MIDI/lilypond tracks are obtained from the Mutopia Project and are either public domain or protected by CCA-SA-3.0 license. Licensing information and other metadata related to the tracks can be found in this document.

 

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Additional details

Funding

UK Research and Innovation
UKRI Centre for Doctoral Training in Artificial Intelligence and Music EP/S022694/1