(newer) MDX23C 5 stem drumsep by jarredou

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Model | yaml | MK Fixed Colab | UVR (not on MVSep) All SDR metrics are better than the previous 6 stem model below:

SDR: kick: 16.66, snare: 11.54, toms 12.34, hihat: 4.04, cymbals: 6.36 (all metrics).

Metric fullness for snare: 25.0361, bleedless for hh: 12.3470, log_wmse for snare: 13.8959

“it's more on the fullness side than bleedless” - from all the metrics, only bleedless for snare is worse than in the previous model:

26.8420 vs 30.4149

“Quite cleaner than the previous [6 stem] one”, “a lot noisier than other drumpsep models, but that's not necessarily a bad thing.”

Possible “UnpicklingError: "invalid load key, '\x0a'."” issue in UVR if you use the old 6 stem yaml.

Maybe if we separate just snare with the old MDX23C model below from an already separated drums stem, and mix/invert to get the rest, then pass it through the new model, the bleed would be gone.

For comparison, metrics of the old 6 stem jarredou/Aufr33 MDX23C model

(which has cymbals divided into ride and crash which are not in the evaluation dataset):

SDR: kick: 14.55, snare: 9.79, toms: 10.64, hihat: 3.20, cymbals: 6.08

Metric fullness for snare: 25.0361, bleedless for hh: 10.2765, log_wmse for snare: 12.4258

The model was trained with a lightweight config to train on a subpar T4 GPU on free Colabs and 10 accounts. The metrics do not surpass exclusive drumsep Mel-Roformer and SCNet models on MVSEP, but at least you can use this one locally.

“Depending on the quality tier of input source material, it can sometimes yield more accurate stem-to-stem separations than either MelRoFormer or SCNet-XL four-or-six stem DrumSep models. (...)

For example, I often find that MelRoFormer DrumSep can leave the upper frequency range of Snare hits and mis-assign them to the Cymbals stem. This is a common issue I have encountered with separating AUD recordings with MelRoFormer DrumSep.

MDX23c 5-stem drumsep is trained in such a way that it separates these snare remainders out of the Cymbals stem, which is extremely useful. " Dyslexicon”