Audio-to-Audio
speechbrain
PyTorch
English
audio-source-separation
Source Separation
Speech Separation
WHAM!
SepFormer
Transformer
Instructions to use speechbrain/sepformer-whamr16k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use speechbrain/sepformer-whamr16k with speechbrain:
from speechbrain.pretrained import SepformerSeparation model = SepformerSeparation.from_hparams( "speechbrain/sepformer-whamr16k" ) model.separate_file("file.wav") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ea19aa6367c6b8e850d2cb5bc0d462d2489310da7d92a806e0c28a0b476d026
- Size of remote file:
- 206 MB
- SHA256:
- 89a9b119d5ce268c345c2ba978e8ff10a13beabc8d6ee1962b256721de9564d6
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