Audiosronnx Deepfilternet
DeepFilterNet3 speech denoiser — the three ONNX graphs its own Rust/tract runtime uses, mirrored for the audiosronnx deepfilternet engine (loaddenoise("deepfilternet")).
Source du modèle
- Type
- Other
- Taille du fichier
- 1,86–3,19 MB
- Version
- vDf dec
- Mis à jour
- 12 oct. 2026
- Source
- Hugging Face
Description de la source
audiosronnx-deepfilternet
DeepFilterNet3 speech denoiser — the three ONNX graphs its own Rust/tract runtime uses,
mirrored for the audiosronnx deepfilternet engine (load_denoise("deepfilternet")).
| graph | inputs | outputs |
|---|---|---|
enc.onnx | feat_erb[1,1,T,32], feat_spec[1,2,T,96] | e0..e3, emb, c0, lsnr |
erb_dec.onnx | emb, e3, e2, e1, e0 | m[1,1,T,32] ERB mask |
df_dec.onnx | emb, c0 | coefs[1,T,96,10] deep-filter taps (freq-major) |
48 kHz. The STFT/ERB frontend and synthesis come from DeepFilterLib (libdf, Rust — no
torch); the mask application and deep filtering run in numpy. Inference is onnxruntime only.
Upstream (unmodified): https://github.com/Rikorose/DeepFilterNet — models/DeepFilterNet3_onnx.tar.gz
Validated: real noisy speech SI-SDR 2.82 -> 11.97 dB (+9.15), corr(clean, denoised) 0.97. Note: denoising degrades ASR (WER 0.533 -> 0.583) — use for perceptual cleanup, not before a recognizer. See the engine's conversion notes.
Sources
1 source
Sources
1 sourceVérifié 12 oct.
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Artefacts du modèle
3 artefacts
Artefacts du modèle
3 artefactsExtraits de sources
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Extraits de sources
2 extraits--- license: mit tags: [audio-to-audio, speech-enhancement, denoising, deepfilternet, onnx] --- # audiosronnx-deepfilternet DeepFilterNet3 speech denoiser — the three ONNX graphs its own Rust/tract runtime uses, mirrored for the `audiosronnx` `deepfilternet` engine (`load_denoise("deepfilternet")`). | graph | inputs | outputs | |---|---|---| | `enc.onnx` | `feat_erb[1,1,T,32]`, `feat_spec[1,2,T,96]` | `e0..e3`, `emb`, `c0`, `lsnr` | | `erb_dec.onnx` | `emb`, `e3`, `e2`, `e1`, `e0` | `m[1,1,T,32]` ERB mask | | `df_dec.onnx` | `emb`, `c0` | `coefs[1,T,96,10]` deep-filter taps (freq-major) | 48 kHz. The STFT/ERB frontend and synthesis come from `DeepFilterLib` (libdf, Rust — no torch); the mask application and deep filtering run in numpy. Inference is onnxruntime only. Upstream (unmodified): https://github.com/Rikorose/DeepFilterNet — `models/DeepFilterNet3_onnx.tar.gz` Validated: real noisy speech SI-SDR 2.82 -> 11.97 dB (+9.15), corr(clean, denoised) 0.97. Note: denoising degrades ASR (WER 0.533 -> 0.583) — use for perceptual cleanup, not before a recognizer. See the engine's conversion notes.
Source context: 0 downloads · 0 likes · Pipeline audio-to-audio · Repo TigreGotico/audiosronnx-deepfilternet
