more emoji

README.md

@@ -51,7 +51,7 @@ An uni-directional model can easily be trained as described [here](docs/training
 
 After applying the LSTM, the signal is decoded back to its original input dimensionality. In the last steps the output is multiplied with the input magnitude spectrogram, so that the models is asked to learn a mask.
 
-## Putting source models together: the `Separator`
+## 🤹‍♀️ Putting source models together: the `Separator`
 
 `models.Separator` puts together _Open-unmix_ spectrogram model for each desired target, and combines their output through a multichannel generalized Wiener filter, before application of inverse STFTs using `torchaudio`.
 The filtering is differentiable (but parameter-free) version of [norbert](https://github.com/sigsep/norbert). The separator is currently currently only used during training.