Create README.md

README.md

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+---
+language: "en"
+thumbnail:
+tags:
+- Source Separation
+- Speech Separation
+- Audio Source Separation
+- WHAM!
+- SepFormer
+- Transformer 
+license: "apache-2.0"
+datasets:
+- WHAM!
+metrics:
+- SI-SNRi
+- SDRi
+
+---
+
+# 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 [WHAM!](http://wham.whisper.ai/) dataset. For a better experience we encourage you to learn more about
+[SpeechBrain](https://speechbrain.github.io). The given model performance is 16.3 dB SI-SNRi on the test set of WHAM! dataset.
+
+| Release | Test-Set SI-SNRi | Test-Set SDRi |
+|:-------------:|:--------------:|:--------------:|
+| 09-03-21 | 16.3 dB | 16.7 dB |
+
+
+## Install SpeechBrain
+
+First of all, please install SpeechBrain with the following command:
+
+```
+pip install \\we hide ! SpeechBrain is still private :p
+```
+
+Please notice that we encourage you to read our tutorials and learn more about
+[SpeechBrain](https://speechbrain.github.io).
+
+### Perform source separation on your own audio file
+
+```python
+
+from speechbrain.pretrained import separator
+import torchaudio
+
+model = separator.from_hparams(source="speechbrain/sepformer-wham")
+
+mix, fs = torchaudio.load("yourspeechbrainpath/samples/audio_samples/test_mixture.wav")
+
+est_sources = model.separate(mix)
+est_sources = est_sources / est_sources.max(dim=1, keepdim=True)[0]
+
+torchaudio.save("source1hat.wav", est_sources[:, :, 0].detach().cpu(), 8000)
+torchaudio.save("source2hat.wav", est_sources[:, :, 1].detach().cpu(), 8000)
+
+```
+
+#### Referencing SpeechBrain
+
+```
+@misc{SB2021,
+    author = {Ravanelli, Mirco and Parcollet, Titouan and Rouhe, Aku and Plantinga, Peter and Rastorgueva, Elena and Lugosch, Loren and Dawalatabad, Nauman and Ju-Chieh, Chou and Heba, Abdel and Grondin, Francois and Aris, William and Liao, Chien-Feng and Cornell, Samuele and Yeh, Sung-Lin and Na, Hwidong and Gao, Yan and Fu, Szu-Wei and Subakan, Cem and De Mori, Renato and Bengio, Yoshua },
+    title = {SpeechBrain},
+    year = {2021},
+    publisher = {GitHub},
+    journal = {GitHub repository},
+    howpublished = {\url{https://github.com/speechbrain/speechbrain}},
+  }
+```
+
+#### Referencing SepFormer
+```
+@inproceedings{subakan2021attention,
+      title={Attention is All You Need in Speech Separation}, 
+      author={Cem Subakan and Mirco Ravanelli and Samuele Cornell and Mirko Bronzi and Jianyuan Zhong},
+      year={2021},
+      booktitle={ICASSP 2021}
+}
+```