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Audiosronnx Deepfilternet

DeepFilterNet3 speech denoiser — the three ONNX graphs its own Rust/tract runtime uses, mirrored for the audiosronnx deepfilternet engine (loaddenoise("deepfilternet")).

KindOtherVersionDf decCgrade

Model source

Kind
Other
File size
1.86–3.19 MB
Version
vDf dec
Updated
Oct 12, 2026
Source
Hugging Face

Source description

audiosronnx-deepfilternet

DeepFilterNet3 speech denoiser — the three ONNX graphs its own Rust/tract runtime uses, mirrored for the audiosronnx deepfilternet engine (load_denoise("deepfilternet")).

graphinputsoutputs
enc.onnxfeat_erb[1,1,T,32], feat_spec[1,2,T,96]e0..e3, emb, c0, lsnr
erb_dec.onnxemb, e3, e2, e1, e0m[1,1,T,32] ERB mask
df_dec.onnxemb, c0coefs[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
Hugging FacePrimaryVersion 9e9bbc9ca4a09fe53440e223abf06f879d91f876
huggingface.co/TigreGotico/audiosronnx-deepfilternet/tree/9e9bbc9ca4a09fe53440e223abf06f879d91f876

Verified Oct 12

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Model artifacts

3 artifacts

df_dec.onnx

onnx · 3.19 MB · SHA-256 23114ce3b0f6…278a · Hugging Face

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enc.onnx

onnx · 1.86 MB · SHA-256 7c5399d3da8a…1916 · Hugging Face

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erb_dec.onnx

onnx · 3.14 MB · SHA-256 ab669a1d10af…d895 · Hugging Face

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Source excerpts

2 excerpts

--- 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