Mel Band Roformer Vocals Onnx
A host-STFT ONNX export of a Mel-Band RoFormer vocal-separation model, used by Silverdaw as its optional higher-quality vocals model. Silverdaw produces the isolated vocal stem with this model; the instrumental side...
Modellquelle
- Art
- Other
- Dateigröße
- 5,06 MB
- Version
- vSyhft core folded fp16 webgpu
- Aktualisiert
- 11. Okt. 2026
- Quelle
- Hugging Face
Quellenbeschreibung
Silverdaw Vocal Quality Pack — Mel-Band RoFormer (ONNX)
A host-STFT ONNX export of a Mel-Band RoFormer vocal-separation model, used by
Silverdaw as its optional higher-quality
vocals model. Silverdaw produces the isolated vocal stem with this model; the
instrumental side is reconstructed as the residual (mix − vocals).
The torch.stft / torch.istft are stripped out of the graph: the ONNX core
consumes a precomputed STFT and returns per-bin complex masks, and the host
application runs the STFT, applies the masks, and runs the iSTFT.
This repository is a re-host of
musetric/vocal-separation-roformer-onnx
so Silverdaw can serve the file from a stable, self-owned location. The weights
and the export are unchanged (byte-identical; same SHA-256).
Files
| File | Size | Notes |
|---|---|---|
syhft_core_folded_fp16_webgpu.onnx | ~5 MB | The neural-core graph. |
syhft_core_folded_fp16_webgpu.onnx.data | ~707 MB | External fp16 weights. Must sit beside the .onnx — the graph references it by exact filename; ONNX Runtime loads it automatically. |
I/O contract (host pipeline)
- STFT —
n_fft = 2048,hop = 441, 44.1 kHz, periodic Hann window, reflect ("centre") padding byn_fft/2. One chunk =hop × (frames − 1)samples (≈ 11 s,frames = 1101). - Tensor —
[1, 2050, 1101, 2]= (batch,(n_fft/2 + 1) × channels, frames, complex), with packed bin index2 × freq + channel. - Mask — the model returns a complex mask of the same shape; the host applies it by complex multiplication onto the STFT, then runs an envelope-normalised iSTFT and a chunk-level overlap-add. Track-level recombination is a Hamming overlap-add (8 s step over the ~11 s window) with peak normalisation.
Provenance & license
License: MIT.
- Weights — © Kimberley Jensen / SYH99999
(
SYH99999/MelBandRoformerBigSYHFTV1Fast; "Kim Vocal 2" / SYHFT lineage). - ONNX export — © musetric
(
musetric/vocal-separation-roformer-onnx). - Architecture — Mel-Band RoFormer (Wang, Lu, Won; arXiv:2310.01809) /
lucidrains/BS-RoFormer(MIT).
Note on training data: the upstream training-data provenance is undocumented; the weights are distributed by their author under MIT. This re-host treats them as MIT-licensed accordingly, the same posture taken by other openly-distributed separation models.
Intended use
Designed for offline (non-real-time) vocal separation inside a desktop DAW. It is not a real-time audio-callback model — run it on a worker/background thread.
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Quellen
1 QuelleVerifiziert 11. Okt.
Modellartefakte
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Modellartefakte
1 Artefaktsyhft_core_folded_fp16_webgpu.onnx
onnx · 5,06 MB · SHA-256 dde2bfe8f85d…e918 · Hugging Face
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Quellenauszüge
2 Auszüge--- license: mit library_name: onnxruntime pipeline_tag: audio-to-audio tags: - onnx - onnxruntime - audio - music - source-separation - stem-separation - mel-band-roformer - roformer - vocals - instrumental --- # Silverdaw Vocal Quality Pack — Mel-Band RoFormer (ONNX) A host-STFT ONNX export of a **Mel-Band RoFormer** vocal-separation model, used by [Silverdaw](https://github.com/irarainey/silverdaw) as its optional higher-quality **vocals** model. Silverdaw produces the isolated vocal stem with this model; the instrumental side is reconstructed as the residual (`mix − vocals`). The `torch.stft` / `torch.istft` are stripped out of the graph: the ONNX core consumes a precomputed STFT and returns per-bin complex masks, and the host application runs the STFT, applies the masks, and runs the iSTFT. This repository is a **re-host** of [`musetric/vocal-separation-roformer-onnx`](https://huggingface.co/musetric/vocal-separation-roformer-onnx) so Silverdaw can serve the file from a stable, self-owned location. The weights and the export are unchanged (byte-identical; same SHA-256). ## Files | File | Size | Notes | | --- | --- | --- | | `syhft_core_folded_fp16_webgpu.onnx` | ~5 MB | The neural-core graph. | | `syhft_core_folded_fp16_webgpu.onnx.data` | ~707 MB | External fp16 weights. **Must sit beside the `.onnx`** — the graph references it by exact filename; ONNX Runtime loads it automatically. | ## I/O contract (host pipeline) - **STFT** — `n_fft = 2048`, `hop = 441`, 44.1 kHz, periodic Hann window, reflect ("centre") padding by `n_fft/2`. One chunk = `hop × (frames − 1)` samples (≈ 11 s, `frames = 1101`). - **Tensor** — `[1, 2050, 1101, 2]` = (batch, `(n_fft/2 + 1) × channels`, frames, complex), with packed bin index `2 × freq + channel`. - **Mask** — the model returns a complex mask of the same shape; the host applies it by complex multiplication onto the STFT, then runs an envelope-normalised iSTFT and a chunk-level overlap-add. Track-level recombination is a Hamming overlap-add (8 s step over the ~11 s window) with peak normalisation. ## Provenance & license **License: MIT.** - **Weights** — © Kimberley Jensen / SYH99999 (`SYH99999/MelBandRoformerBigSYHFTV1Fast`; "Kim Vocal 2" / SYHFT lineage). - **ONNX export** — © musetric ([`musetric/vocal-separation-roformer-onnx`](https://huggingface.co...
Source context: 0 downloads · 1 likes · Pipeline audio-to-audio · Library onnxruntime · Repo silverdaw/mel-band-roformer-vocals-onnx
