You can deploy this model and start earning money today!

TigreGotico/
audiosronnx-dpdfnet

Name: audiosronnx-dpdfnet
Availability: InStock

Views

No views yet

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).

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.

TigreGotico/audiosronnx-dpdfnet

audiosronnx-dpdfnet

Usage

License

TigreGotico/
audiosronnx-dpdfnet