where S𝑖𝑛𝑠𝑡𝑟(n) is the waveform of the ground truth and Ŝ𝑖𝑛𝑠𝑡𝑟(𝑛) denotes the waveform of the estimate. The higher the SDR score, the better the output of the system is.
where $S_{instr}(n)$ is the waveform of the ground truth and Ŝ𝑖𝑛𝑠𝑡𝑟(𝑛) denotes the waveform of the estimate. The higher the SDR score, the better the output of the system is.
In order to rank systems, we will use the average SDR computed by
for each song. Finally, the overall score is obtained by averaging SDRsong over all songs in the hidden test set.
# Baselines
TODO: To be added
We use Open-Unmix for the baseline. Specifically, we provide trained checkpoints for the UMXL model. You can use the baseline by switching to the openunmix-baseline branch on this repository. To test the models locally, you need to install `git-lfs`.