  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.
