Audio-to-Audio
speechbrain
English
audio-source-separation
Source Separation
Speech Separation
Audio Source Separation
WHAM!
SepFormer
Transformer
Instructions to use speechbrain/sepformer-wham with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use speechbrain/sepformer-wham with speechbrain:
from speechbrain.pretrained import SepformerSeparation model = SepformerSeparation.from_hparams( "speechbrain/sepformer-wham" ) model.separate_file("file.wav") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21b0c553f7b5c2ddc515e3f10165e59098fbee413b5a9354ee7a016cc3822757
- Size of remote file:
- 17.3 kB
- SHA256:
- d9a06998d188f9fa0cb79915dc855aac4737c41392488b11d500b453000f4dfa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.