| | --- |
| | license: mit |
| | --- |
| | |
| | This is a pre-trained version of Fast FullSubNet, trained on the Deep Noise Suppression Challenge dataset of 2020 (DNS-INTERSPEECH-2020). |
| |
|
| | # Instructions |
| |
|
| | https://fullsubnet.readthedocs.io/en/latest/usage/getting_started.html |
| | |
| | # Code |
| | |
| | https://github.com/Audio-WestlakeU/FullSubNet |
| | |
| | # Paper |
| | |
| | [Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech Enhancement |
| | Xiang Hao, Xiaofei Li](https://arxiv.org/abs/2212.09019) |
| | |
| | # Performance |
| | |
| | | | With Reverb | | | | No Reverb | | | |
| | -- | -- | -- | -- | -- | -- | -- | -- |
| | Method | WB-PESQ | NB-PESQ | SI-SDR | STOI | WB-PESQ | NB-PESQ | SI-SDR | STOI |
| | Fast FullSubNet (118 Epochs) | 2.882 | 3.42 | 15.33 | 0.9233 | 2.694 | 3.222 | 16.34 | 0.9571 |
| | [FullSubNet (58 Epochs)](https://github.com/Audio-WestlakeU/FullSubNet/releases/tag/v0.2) (just for comparison) | 2.987 | 3.496 | 15.756 | 0.926 | 2.889 | 3.385 | 17.635 | 0.964 |
