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@@ -20,11 +20,11 @@ metrics:
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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 22.5 dB on the test set of WSJ0-2Mix dataset.
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  | Release | Test-Set SI-SNR | Test-Set SDR |
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  |:-------------:|:--------------:|:--------------:|
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- | 09-03-21 | 22.5dB | 22.7dB |
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  ## Install SpeechBrain
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  model = separator.from_hparams(source="speechbrain/sepformer-wsj02mix")
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- mix, fs = torchaudio.load("test_mixture.wav")
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  est_sources = model.separate(mix)
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  est_sources = est_sources / est_sources.max(dim=1, keepdim=True)[0]
 
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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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  | Release | Test-Set SI-SNR | Test-Set SDR |
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  |:-------------:|:--------------:|:--------------:|
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+ | 09-03-21 | 22.4dB | 22.6dB |
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  ## Install SpeechBrain
 
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  model = separator.from_hparams(source="speechbrain/sepformer-wsj02mix")
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+ mix, fs = torchaudio.load("samples/audio_samples/test_mixture.wav")
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  est_sources = model.separate(mix)
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  est_sources = est_sources / est_sources.max(dim=1, keepdim=True)[0]