/FullSubNet

PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."

Primary LanguagePythonMIT LicenseMIT

FullSubNet

Official PyTorch implementation of FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement, ICASSP 2021.

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Guides

Key Features

You can use all of these things:

  • Available models

    • Fullband Baseline
    • FullSubNet
    • FullSubNet (lightweight)
    • Delayed Sub-Band LSTM

  • Available datasets

    • Deep Noise Suppression Challenge - INTERSPEECH 2020
    • Demand + CSTR VCTK Corpus

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 respository Under the MIT license.