speechbrain
/

sepformer-whamr

Audio-to-Audio speechbrain English Source Separation Speech Separation Audio Source Separation WHAM! SepFormer Transformer audio-source-separation

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cemsubakan commited on Oct 7, 2021

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@@ -23,7 +23,7 @@ metrics:
 <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
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-# SepFormer trained on WHAM!
 This repository provides all the necessary tools to perform audio source separation with a [SepFormer](https://arxiv.org/abs/2010.13154v2) model, implemented with SpeechBrain, and pretrained on [WHAMR!](http://wham.whisper.ai/) dataset, which is basically a version of WSJ0-Mix dataset with environmental noise and reverberation. For a better experience we encourage you to learn more about [SpeechBrain](https://speechbrain.github.io). The  model performance is 13.7 dB SI-SNRi on the test set of WHAMR! dataset.
 | Release | Test-Set SI-SNRi | Test-Set SDRi |

 <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
 <br/><br/>
+# SepFormer trained on WHAMR!
 This repository provides all the necessary tools to perform audio source separation with a [SepFormer](https://arxiv.org/abs/2010.13154v2) model, implemented with SpeechBrain, and pretrained on [WHAMR!](http://wham.whisper.ai/) dataset, which is basically a version of WSJ0-Mix dataset with environmental noise and reverberation. For a better experience we encourage you to learn more about [SpeechBrain](https://speechbrain.github.io). The  model performance is 13.7 dB SI-SNRi on the test set of WHAMR! dataset.
 | Release | Test-Set SI-SNRi | Test-Set SDRi |