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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...

KindOtherVersionSyhft core folded fp16 webgpuBgrade

Model source

Kind
Other
File size
5.06 MB
Version
vSyhft core folded fp16 webgpu
Updated
Oct 11, 2026
Source
Hugging Face

Source description

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

FileSizeNotes
syhft_core_folded_fp16_webgpu.onnx~5 MBThe neural-core graph.
syhft_core_folded_fp16_webgpu.onnx.data~707 MBExternal 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.

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.

Sources

1 source
Hugging FacePrimaryVersion 6baa633eadde3c111041a81a28ed6245f19858ae
huggingface.co/silverdaw/mel-band-roformer-vocals-onnx/tree/6baa633eadde3c111041a81a28ed6245f19858ae

Verified Oct 11

Model artifacts

1 artifact

syhft_core_folded_fp16_webgpu.onnx

onnx · 5.06 MB · SHA-256 dde2bfe8f85d…e918 · Hugging Face

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Source excerpts

2 excerpts

--- 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