---
license: mit
library_name: audiosronnx
pipeline_tag: audio-to-audio
tags:
  - speech-enhancement
  - denoising
  - noise-suppression
  - on-device
  - onnx
---

# audiosronnx-gtcrn

ONNX weights for the **`gtcrn`** denoise engine in
[audiosronnx](https://github.com/TigreGotico/audiosronnx) — a mirror of the streaming
GTCRN graph from [Xiaobin-Rong/gtcrn](https://github.com/Xiaobin-Rong/gtcrn) (MIT).

GTCRN (*Grouped Temporal Convolutional Recurrent Network*) is an ultra-light 16 kHz
speech denoiser — **23.7 K parameters, 33 MMACs/s, ~0.5 MB** — intended for embedded and
on-device use. The graph is stateful and consumes one STFT frame at a time:

```
mix[1, 257, 1, 2], conv_cache, tra_cache, inter_cache
    -> enh[1, 257, 1, 2], conv_cache_out, tra_cache_out, inter_cache_out
```

The ERB filterbank and subband feature extraction live inside the graph; only a sqrt-Hann
STFT/ISTFT runs outside it, in numpy, so inference is onnxruntime-only.

| File | Rate | Size |
|------|------|------|
| `gtcrn_simple.onnx` | 16 kHz | 0.54 MB |

## Usage

```python
from audiosronnx import load_denoise

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

## License

MIT, inherited from the upstream GTCRN release.