  Music source separation is the task of extracting an estimate of one or more
isolated sources or instruments (for example, drums or vocals) from musical
audio. The task of music demixing or unmixing considers the case where the
musical audio is separated into an estimate of all of its constituent sources
that can be summed back to the original mixture. The Music Demixing Challenge
was created to inspire new demixing research. Open-Unmix (UMX), and the
improved variant CrossNet-Open-Unmix (X-UMX), were included in the challenge as
the baselines. Both models use the Short-Time Fourier Transform (STFT) as the
representation of music signals. The time-frequency uncertainty principle
states that the STFT of a signal cannot have maximal resolution in both time
and frequency. The tradeoff in time-frequency resolution can significantly
affect music demixing results. Our proposed adaptation of UMX replaced the STFT
with the sliCQT, a time-frequency transform with varying time-frequency
resolution. Unfortunately, our model xumx-sliCQ achieved lower demixing scores
than UMX.
