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Audiosronnx Frcrn

ONNX export of FRCRNSE16K from ClearerVoice-Studio (Alibaba, Apache-2.0), for the frcrn denoise engine in audiosronnx.

TipoOtherVersãoFrcrnCnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
54,8 MB
Versão
vFrcrn
Atualizado
12 de out. de 2026
Fonte
Hugging Face

Descrição da fonte

audiosronnx-frcrn

ONNX export of FRCRN_SE_16K from ClearerVoice-Studio (Alibaba, Apache-2.0), for the frcrn denoise engine in audiosronnx.

FRCRN (Frequency Recurrent CRN) placed 2nd in the 2022 DNS Challenge and reports PESQ 3.23 / STOI 0.95 / SI-SDR 19.22 on VoiceBank+DEMAND.

The graph is waveform-to-waveform at 16 kHz with a dynamic length axis:

noisy[1, T]  ->  enhanced[1, T]

Its STFT/ISTFT are ConvSTFT/ConviSTFT — Conv1d layers with Fourier kernels, not torch.stft — so the whole two-UNet complex-mask pipeline exports as one static graph and inference is onnxruntime-only.

FileRateSize
frcrn.onnx16 kHz57.5 MB

Validated against the upstream ClearerVoice pipeline end-to-end: correlation 0.99999994, 57.6 dB SNR (residual is fp32 rounding).

Usage

from audiosronnx import load_denoise

dn = load_denoise("frcrn")
clean, rate = dn.denoise("noisy.wav")   # -> (float32 mono, 16000)

License

Apache-2.0, inherited from ClearerVoice-Studio.

Fontes

1 fonte
Hugging FacePrimárioVersão 8d80ae92591dce122c8d59b02886095cd4192c29
huggingface.co/TigreGotico/audiosronnx-frcrn/tree/8d80ae92591dce122c8d59b02886095cd4192c29

Verificado 12 de out.

Artefatos de modelo

1 artefato

frcrn.onnx

onnx · 54,8 MB · SHA-256 9a3582e61901…c7f6 · Hugging Face

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Trechos de fonte

2 trechos

--- license: apache-2.0 library_name: audiosronnx pipeline_tag: audio-to-audio tags: - speech-enhancement - denoising - noise-suppression - onnx --- # audiosronnx-frcrn ONNX export of **FRCRN_SE_16K** from [ClearerVoice-Studio](https://github.com/modelscope/ClearerVoice-Studio) (Alibaba, Apache-2.0), for the `frcrn` denoise engine in [audiosronnx](https://github.com/TigreGotico/audiosronnx). FRCRN (*Frequency Recurrent CRN*) placed 2nd in the 2022 DNS Challenge and reports **PESQ 3.23 / STOI 0.95 / SI-SDR 19.22** on VoiceBank+DEMAND. The graph is waveform-to-waveform at 16 kHz with a dynamic length axis: ``` noisy[1, T] -> enhanced[1, T] ``` Its STFT/ISTFT are `ConvSTFT`/`ConviSTFT` — Conv1d layers with Fourier kernels, not `torch.stft` — so the whole two-UNet complex-mask pipeline exports as one static graph and inference is onnxruntime-only. | File | Rate | Size | |------|------|------| | `frcrn.onnx` | 16 kHz | 57.5 MB | Validated against the upstream ClearerVoice pipeline end-to-end: **correlation 0.99999994, 57.6 dB SNR** (residual is fp32 rounding). ## Usage ```python from audiosronnx import load_denoise dn = load_denoise("frcrn") clean, rate = dn.denoise("noisy.wav") # -> (float32 mono, 16000) ``` ## License Apache-2.0, inherited from ClearerVoice-Studio.

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