Lightweight-Speech-Denoising.axera

Lightweight-Speech-Denoising

This project provides lightweight speech enhancement (denoising) models optimized for Axera NPU platforms, combining the DSP framework of RNNoise and the model architecture of GTCRN.

Key Features

• Good Denoising Quality — Built on GTCRN and RNNoise frameworks; strong noise suppression even at very low parameter counts.
• Ultra-Lightweight Models — Smallest model under 100 KB; CMM memory footprint below 150 KB.
• Minimal Operators — tiny_v5 and conv_se are pure convolutional models with very few operator types; tiny_v5 supports quantization on the operator-limited AX525 platform.
• End-to-End Workflow — Full pipeline. Full project with export / quantization scripts
• Multi-Platform Support — Board inference validated on AX620Q, AX630C, and AX650; PTQ quantization also available for AX620L, AX637, and AX525.

Convert tools links

For those interested in model conversion, refer to:

• Pulsar2 Docs — How to Convert ONNX to axmodel
• Full project with export / quantization scripts

Support Platform

• AX650
  • M4N-Dock（爱芯派Pro）
  • M.2 Accelerator Card
• AX630C
  • 爱芯派2
  • Module-LLM
  • LLM630 Compute Kit
• AX620Q
• AX620L
• AX637
• AX525（only for tiny_v5）

How to use

Directory layout on device:

root@ax650:~# tree Lightweight-Speech-Denoising.axera
Lightweight-Speech-Denoising.axera
├── README.md
├── axmodels
│   ├── ax525_tiny_v5_setrain.axmodel
│   ├── ax620E_conv_se_setrain.axmodel
│   ├── ax620E_gtcrn_setrain.axmodel
│   ├── ax620E_tiny_v5_setrain.axmodel
│   ├── ax620L_conv_se_setrain.axmodel
│   ├── ax620L_gtcrn_setrain.axmodel
│   ├── ax620L_tiny_v5_setrain.axmodel
│   ├── ax637_conv_se_setrain.axmodel
│   ├── ax637_gtcrn_setrain.axmodel
│   ├── ax637_tiny_v5_setrain.axmodel
│   ├── ax630c_conv_se_setrain.axmodel
│   ├── ax630c_gtcrn_setrain.axmodel
│   ├── ax630c_tiny_v5_setrain.axmodel
│   ├── ax650_conv_se_setrain.axmodel
│   ├── ax650_gtcrn_setrain.axmodel
│   └── ax650_tiny_v5_setrain.axmodel
├── build_ax620q
│   └── test_se_denoise_ax
├── build_ax630c
│   └── test_se_denoise_ax
├── build_ax650
│   └── test_se_denoise_ax
├── models
│   ├── conv_se_ax650_config.ini
│   ├── gtcrn_7input_ax650_config.ini
│   ├── tiny_v5_ax650_config.ini
│   └── ...
├── run_ax620q_all.sh
├── run_ax630c_all.sh
├── run_ax650_all.sh
└── test_wavs
    └── mix.wav

Download all files from this repository to the device, then run the corresponding script for your platform:

# AX650
sh run_ax650_all.sh

# AX630C
sh run_ax630c_all.sh

# AX620Q
sh run_ax620q_all.sh

Output .wav files will be saved to output/<platform>_all/.

Inference Results

tiny_v5

conv_se

GTCRN

Test audio: mix.wav, duration 9.77s, 16kHz mono.

TODO

• AX525 board inference (quantization done)
• AX620L board inference (quantization done)
• AX637 board inference (quantization done)

References

• RNNoise — Mozilla open-source DSP + RNN noise suppression framework; STFT/iSTFT and kiss_fft implementation reused in this project. https://github.com/xiph/rnnoise

• GTCRN — Lightweight Gated Temporal Convolutional Recurrent Network for speech enhancement. https://github.com/Xiaobin-Rong/gtcrn