FullSubNet
PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
Install / Use
/learn @Audio-WestlakeU/FullSubNetREADME
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<h1>
FullSubNet
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<p>
Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement
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<a href="https://github.com/haoxiangsnr/FullSubNet/"><img src="https://img.shields.io/badge/Platform-linux-lightgrey" alt="version"></a>
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<a href="https://github.com/haoxiangsnr/FullSubNet/"><img src="https://img.shields.io/badge/Python-3.10-orange" alt="version"></a>
<a href="https://github.com/haoxiangsnr/FullSubNet/"><img src="https://img.shields.io/badge/PyTorch-1.12-brightgreen" alt="python"></a>
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Guides
The documentation is hosted on Read the Docs. Check the documentation for how to train and test models.
- Improved FullSubNet: Further reduces computational costs and enables high sampling rate data processing, e.g., 48 KHz and 24 KHz.
- 📰 FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement, ICASSP 2021
- 📰 Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech Enhancement
- cIRM-based Fullband baseline model (described in the original FullSubNet paper)
Citation
If you use this code for your research, please consider citeing:
@INPROCEEDINGS{hao2020fullsubnet,
author={Hao, Xiang and Su, Xiangdong and Horaud, Radu and Li, Xiaofei},
booktitle={ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={Fullsubnet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement},
year={2021},
pages={6633-6637},
doi={10.1109/ICASSP39728.2021.9414177}
}
License
This repository Under the MIT license.
