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Audiosronnx Dpdfnet

ONNX weights for the dpdfnet denoise engine in audiosronnx — a mirror of Ceva-IP/DPDFNet (Apache-2.0), pinned so the library can resolve a fixed revision.

ArtOtherVersionBaselineBBewertung

Modellquelle

Art
Other
Dateigröße
8,32–14,2 MB
Version
vBaseline
Aktualisiert
12. Okt. 2026
Quelle
Hugging Face

Quellenbeschreibung

audiosronnx-dpdfnet

ONNX weights for the dpdfnet denoise engine in audiosronnx — a mirror of Ceva-IP/DPDFNet (Apache-2.0), pinned so the library can resolve a fixed revision.

DPDFNet (Dual-Path RNN-based DeepFilterNet) is a streaming speech denoiser built on DeepFilterNet2. Each graph is stateful and consumes one STFT frame at a time:

spec[1, 1, F, 2], state[S]  ->  spec_e[1, 1, F, 2], state[S]

The Vorbis-windowed STFT/ISTFT runs in numpy inside audiosronnx, so inference is onnxruntime-only — no torch, and no libdf (unlike the DeepFilterNet3 engine).

FileRateSize
baseline.onnx16 kHz8.7 MB
dpdfnet2.onnx16 kHz10.2 MB
dpdfnet4.onnx16 kHz11.6 MB
dpdfnet8.onnx16 kHz14.5 MB
dpdfnet2_8khz.onnx8 kHz10.2 MB
dpdfnet8_8khz.onnx8 kHz14.6 MB
dpdfnet2_48khz_hr.onnx48 kHz10.5 MB
dpdfnet8_48khz_hr.onnx48 kHz14.9 MB

The adapter reproduces the upstream reference implementation to max abs err 1.7e-8 (correlation 1.000000) on identical input.

Usage

from audiosronnx import load_denoise

dn = load_denoise("dpdfnet")                          # dpdfnet2_48khz by default
clean, rate = dn.denoise("noisy_call.wav")

dn = load_denoise("dpdfnet", model="dpdfnet8")        # 16 kHz, highest quality
dn = load_denoise("dpdfnet", attn_limit_db=12)        # keep a natural noise floor

License

Apache-2.0, inherited from the upstream DPDFNet release.

Quellen

1 Quelle
Hugging FacePrimärVersion e1b60686e2d6c7bdf2376bef189c670755d94a2c
huggingface.co/TigreGotico/audiosronnx-dpdfnet/tree/e1b60686e2d6c7bdf2376bef189c670755d94a2c

Verifiziert 12. Okt.

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Modellartefakte

8 Artefakte

baseline.onnx

onnx · 8,32 MB · SHA-256 371d26182aff…55e0 · Hugging Face

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dpdfnet2_48khz_hr.onnx

onnx · 10,0 MB · SHA-256 7f0575a5cec0…c14b · Hugging Face

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dpdfnet2_8khz.onnx

onnx · 9,72 MB · SHA-256 6218f1dbd6e4…5c5d · Hugging Face

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dpdfnet2.onnx

onnx · 9,71 MB · SHA-256 4f0ee28935b4…c94c · Hugging Face

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dpdfnet4.onnx

onnx · 11,1 MB · SHA-256 42a386d36019…6c01 · Hugging Face

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dpdfnet8_48khz_hr.onnx

onnx · 14,2 MB · SHA-256 7b3afbb260a0…5631 · Hugging Face

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dpdfnet8_8khz.onnx

onnx · 13,9 MB · SHA-256 c061bcc56b80…ea62 · Hugging Face

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dpdfnet8.onnx

onnx · 13,9 MB · SHA-256 899d4f23f3ff…26cb · Hugging Face

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Quellenauszüge

2 Auszüge

--- license: apache-2.0 library_name: audiosronnx pipeline_tag: audio-to-audio tags: - speech-enhancement - denoising - noise-suppression - streaming - onnx --- # audiosronnx-dpdfnet ONNX weights for the **`dpdfnet`** denoise engine in [audiosronnx](https://github.com/TigreGotico/audiosronnx) — a mirror of [Ceva-IP/DPDFNet](https://huggingface.co/Ceva-IP/DPDFNet) (Apache-2.0), pinned so the library can resolve a fixed revision. DPDFNet (*Dual-Path RNN-based DeepFilterNet*) is a streaming speech denoiser built on DeepFilterNet2. Each graph is stateful and consumes one STFT frame at a time: ``` spec[1, 1, F, 2], state[S] -> spec_e[1, 1, F, 2], state[S] ``` The Vorbis-windowed STFT/ISTFT runs in numpy inside audiosronnx, so inference is onnxruntime-only — no torch, and no `libdf` (unlike the DeepFilterNet3 engine). | File | Rate | Size | |------|------|------| | `baseline.onnx` | 16 kHz | 8.7 MB | | `dpdfnet2.onnx` | 16 kHz | 10.2 MB | | `dpdfnet4.onnx` | 16 kHz | 11.6 MB | | `dpdfnet8.onnx` | 16 kHz | 14.5 MB | | `dpdfnet2_8khz.onnx` | 8 kHz | 10.2 MB | | `dpdfnet8_8khz.onnx` | 8 kHz | 14.6 MB | | `dpdfnet2_48khz_hr.onnx` | 48 kHz | 10.5 MB | | `dpdfnet8_48khz_hr.onnx` | 48 kHz | 14.9 MB | The adapter reproduces the upstream reference implementation to **max abs err 1.7e-8** (correlation 1.000000) on identical input. ## Usage ```python from audiosronnx import load_denoise dn = load_denoise("dpdfnet") # dpdfnet2_48khz by default clean, rate = dn.denoise("noisy_call.wav") dn = load_denoise("dpdfnet", model="dpdfnet8") # 16 kHz, highest quality dn = load_denoise("dpdfnet", attn_limit_db=12) # keep a natural noise floor ``` ## License Apache-2.0, inherited from the upstream DPDFNet release.

Source context: 0 downloads · 0 likes · Pipeline audio-to-audio · Library audiosronnx · Repo TigreGotico/audiosronnx-dpdfnet