Actually create README.md

README.md

@@ -0,0 +1,79 @@
+---
+language: "en"
+tags:
+- Robust ASR
+- Speech Enhancement
+- PyTorch
+license: "apache-2.0"
+datasets:
+- Voicebank
+- DEMAND
+metrics:
+- WER
+- PESQ
+- eSTOI
+---
+
+# 1D CNN + Transformer Trained w/ Mimic Loss
+
+This repository provides all the necessary tools to perform enhancement and
+robust ASR training (EN) within
+SpeechBrain. For a better experience we encourage you to learn more about
+[SpeechBrain](https://speechbrain.github.io). The given model performance is:
+
+| Release | Test PESQ | Test eSTOI | Valid WER | Test WER |
+|:-----------:|:-----:| :-----:|:----:|:---------:|
+| 21-03-08 | 2.92 | 85.2 | 3.20 | 2.96 |
+
+## Pipeline description
+
+The mimic loss training system consists of three steps:
+
+1. A perceptual model is pre-trained on clean speech features, the
+same type used for the enhancement masking system.
+2. An enhancement model is trained with mimic loss, using the
+pre-trained perceptual model.
+3. A large ASR model pre-trained on LibriSpeech is fine-tuned
+using the enhancement front-end.
+
+The enhancement and ASR models can be used together or
+independently.
+
+## 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).
+
+## Referencing Mimic Loss
+
+If you find mimic loss useful, please cite:
+
+```
+@inproceedings{bagchi2018spectral,
+title={Spectral Feature Mapping with Mimic Loss for Robust Speech Recognition},
+author={Bagchi, Deblin and Plantinga, Peter and Stiff, Adam and Fosler-Lussier, Eric},
+booktitle={IEEE Conference on Audio, Speech, and Signal Processing (ICASSP)},
+year={2018}
+}
+```
+
+## Referencing SpeechBrain
+
+If you find SpeechBrain useful, please cite:
+
+```
+@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}},
+}
+```