@@ -32,9 +32,14 @@ Please also check out our follow-up work with code available:
...
@@ -32,9 +32,14 @@ Please also check out our follow-up work with code available:
## Pretrained checkpoints
## Pretrained checkpoints
- For the speech enhancement task, we offer pretrained checkpoints for models that have been trained on the VoiceBank-DEMAND and WSJ0-CHiME3 datasets, as described in our journal paper [2]. You can download them [here](https://drive.google.com/drive/folders/1CSnkhUSoiv3RG0xg7WEcVapyLuwDaLbe?usp=sharing).
- For the speech enhancement task, we offer pretrained checkpoints for models that have been trained on the VoiceBank-DEMAND and WSJ0-CHiME3 datasets, as described in our journal paper [2]. You can download them [here](https://drive.google.com/drive/folders/1CSnkhUSoiv3RG0xg7WEcVapyLuwDaLbe?usp=sharing).
- SGMSE+ trained on VoiceBank-DEMAND: `gdown 1_H3EXvhcYBhOZ9QNUcD5VZHc6ktrRbwQ`
- SGMSE+ trained on WSJ0-CHiME3: `gdown 16K4DUdpmLhDNC7pJhBBc08pkSIn_yMPi`
- For the dereverberation task, we offer a checkpoint trained on our WSJ0-REVERB dataset. You can download it [here](https://drive.google.com/drive/folders/1082_PSEgrqoVVrNsAkSIcpLF1AAtzGwV?usp=sharing).
- For the dereverberation task, we offer a checkpoint trained on our WSJ0-REVERB dataset. You can download it [here](https://drive.google.com/drive/folders/1082_PSEgrqoVVrNsAkSIcpLF1AAtzGwV?usp=sharing).
- SGMSE+ trained on WSJ0-REVERB: `gdown 1eiOy0VjHh9V9ZUFTxu1Pq2w19izl9ejD`
- Note that this checkpoint works better with sampler settings `--N 50 --snr 0.33`.
- Note that this checkpoint works better with sampler settings `--N 50 --snr 0.33`.
- For 48 kHz models [3], we offer pretrained checkpoints for speech enhancement, trained on the EARS-WHAM dataset, and for dereverberation, trained on the EARS-Reverb dataset. You can download them [here](https://drive.google.com/drive/folders/1Tn6pVwjxUAy1DJ8167JCg3enuSi0hiw5?usp=sharing).
- For 48 kHz models [3], we offer pretrained checkpoints for speech enhancement, trained on the EARS-WHAM dataset, and for dereverberation, trained on the EARS-Reverb dataset. You can download them [here](https://drive.google.com/drive/folders/1Tn6pVwjxUAy1DJ8167JCg3enuSi0hiw5?usp=sharing).
- SGMSE+ trained on EARS-WHAM: `gdown 1t_DLLk8iPH6nj8M5wGeOP3jFPaz3i7K5`
- SGMSE+ trained on EARS-Reverb: `1PunXuLbuyGkknQCn_y-RCV2dTZBhyE3V`
Usage:
Usage:
- For resuming training, you can use the `--ckpt` option of `train.py`.
- For resuming training, you can use the `--ckpt` option of `train.py`.
