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frcrn denoise engine in
audiosronnx.noisy[1, T] -> enhanced[1, T]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 |
1from audiosronnx import load_denoise
2
3dn = load_denoise("frcrn")
4clean, rate = dn.denoise("noisy.wav") # -> (float32 mono, 16000)