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Sound Demixing Challenge 2023 Music Demixing Track Technical Report: TFC-TDF-UNet v3

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In this report, we present our award-winning solutions for the Music Demixing Track of Sound Demixing Challenge 2023. First, we propose TFC-TDF-UNet v3, a time-efficient music source separation model that achieves state-of-the-art results on the MUSDB benchmark. We then give full details regarding our solutions for each Leaderboard, including a loss masking approach for noise-robust training. Code for reproducing model training and final submissions is available at github.com/kuielab/sdx23.

Minseok Kim, Jun Hyung Lee, Soonyoung Jung• 2023

Related benchmarks

TaskDatasetResultRank
Music Source SeparationMUSDB18 HQ (test)
SDR (Drums)8.96
61
Vocal Source SeparationMUSDB HQ 18
cSDR9.59
14
Music Source SeparationMDX Challenge Leaderboard C 2021 1.0 (test)
SDR (Vocals)9.65
5
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Code

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