Update README.md

README.md

@@ -18,9 +18,7 @@ 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 [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.
+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, which is basically a version of WSJ0-Mix dataset with environmental noise. 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 |
 |:-------------:|:--------------:|:--------------:|
@@ -35,8 +33,7 @@ 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).
+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