Audio-to-Audio
speechbrain
English
Source Separation
Speech Separation
Audio Source Separation
WSJ02Mix
SepFormer
Transformer
audio-source-separation
Instructions to use speechbrain/sepformer-wsj02mix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use speechbrain/sepformer-wsj02mix with speechbrain:
from speechbrain.pretrained import SepformerSeparation model = SepformerSeparation.from_hparams( "speechbrain/sepformer-wsj02mix" ) model.separate_file("file.wav") - Notebooks
- Google Colab
- Kaggle
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README.md
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tags:
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- Source Separation
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- Speech Separation
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- WSJ02Mix
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- SepFormer
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- Transformer
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# SepFormer trained on WSJ0-2Mix
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This repository provides all the necessary tools to perform source separation with a [SepFormer](https://arxiv.org/abs/2010.13154v2)
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model, implemented with SpeechBrain, and pretrained on WSJ0-2Mix dataset. For a better experience we encourage you to learn more about
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[SpeechBrain](https://speechbrain.github.io). The given model performance is 22.4 dB on the test set of WSJ0-2Mix dataset.
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tags:
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- Source Separation
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- Speech Separation
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- Audio Source Separation
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- WSJ02Mix
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- SepFormer
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- Transformer
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# SepFormer trained on WSJ0-2Mix
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This repository provides all the necessary tools to perform audio source separation with a [SepFormer](https://arxiv.org/abs/2010.13154v2)
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model, implemented with SpeechBrain, and pretrained on WSJ0-2Mix dataset. For a better experience we encourage you to learn more about
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[SpeechBrain](https://speechbrain.github.io). The given model performance is 22.4 dB on the test set of WSJ0-2Mix dataset.
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