Spleeter 2stems for Core ML (vocal mask, 1536 bins, FP16)
A Core ML conversion of Spleeter's pretrained 2stems model (v1.4.0) by Deezer, used to separate voice from music in Clarity Sound Studio, a free, open-source macOS app.
| File | Spleeter2StemsVocalMask-F1536-fp16.mlmodelc (compiled ML Program, FP16, macOS 14+) |
| Upstream | 2stems.tar.gz, SHA-256 f3a90b39dd2874269e8b05a48a86745df897b848c61f3958efc80a39152bd692 |
| Conversion | The two U-Nets re-implemented in PyTorch (matching TensorFlow at a median 72 dB SNR), then spleeter_torch.py convert --f-bins 1536 with coremltools and coremlcompiler |
| Input | magnitude, float32 (1, 2, 512, 1536): a stereo magnitude spectrogram |
| Output | vocal_mask, float32, same shape: the vocal ratio mask, sv² / (sv² + sa² + 1e-6) |
The weights are unchanged apart from the conversion to FP16.
Licence
MIT licence; see LICENSE. Copyright (c) 2019-present Deezer SA.
R. Hennequin, A. Khlif, F. Voituret and M. Moussallam, "Spleeter: a fast and efficient music source separation tool with pre-trained models", Journal of Open Source Software 5(50), 2154, 2020.
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