Update README.md

README.md

@@ -20,6 +20,7 @@ metrics:
 # 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 with 16k sampling frequency, which is basically a version of WSJ0-Mix dataset with environmental noise and reverberation in 16k. For a better experience we encourage you to learn more about [SpeechBrain](https://speechbrain.github.io). The given model performance is 13.5 dB SI-SNRi on the test set of WHAMR! dataset.
 
+
 | Release | Test-Set SI-SNRi | Test-Set SDRi |
 |:-------------:|:--------------:|:--------------:|
 | 30-03-21 | 13.5 dB | 13.0 dB |
@@ -61,7 +62,7 @@ torchaudio.save("source2hat.wav", est_sources[:, :, 1].detach().cpu(), 16000)
     year = {2021},
     publisher = {GitHub},
     journal = {GitHub repository},
-    howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
+    howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
   }
 ```