Update README.md

README.md

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----
-language: "en"
-thumbnail:
-pipeline_tag: automatic-speech-recognition
-tags:
-- CTC
-- Attention
-- pytorch
-- speechbrain
-- Transformer
-license: "apache-2.0"
-datasets:
-- commonvoice
-metrics:
-- wer
-- cer
----
-
-<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
-<br/><br/>
-
-# Work in Progress
-
-### Limitations
-The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
-
-# **About SpeechBrain**
-- Website: https://speechbrain.github.io/
-- Code: https://github.com/speechbrain/speechbrain/
-- HuggingFace: https://huggingface.co/speechbrain/
-
-
-# **Citing SpeechBrain**
-Please, cite SpeechBrain if you use it for your research or business.
-
-```bibtex
-@misc{speechbrain,
-  title={{SpeechBrain}: A General-Purpose Speech Toolkit},
-  author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
-  year={2021},
-  eprint={2106.04624},
-  archivePrefix={arXiv},
-  primaryClass={eess.AS},
-  note={arXiv:2106.04624}
-}
+# Vocoder with HiFIGAN trained on LJSpeech
+
+This repository provides all the necessary tools for using a [HiFIGAN](https://arxiv.org/abs/2010.05646) vocoder trained with [LJSpeech](https://keithito.com/LJ-Speech-Dataset/). 
+
+The pre-trained model takes in input a spectrogram and produces a waveform in output. Typically, a vocoder is used after a TTS model that converts an input text into a spectrogram.
+
+
+## Install SpeechBrain
+
+First of all, currently, you need to install SpeechBrain from the source:
+
+1. Clone SpeechBrain:
+
+```bash
+git clone https://github.com/speechbrain/speechbrain/
+```
+
+2. Install it:
+
+```
+cd speechbrain
+pip install -r requirements.txt
+pip install -e .
+```
+
+Please notice that we encourage you to read our tutorials and learn more about
+[SpeechBrain](https://speechbrain.github.io).
+
+### Using the Vocoder
+
+```
+from speechbrain.pretrained import HIFIGAN
+hifi_gan = HIFIGAN.from_hparams(source="speechbrain/Vocoder_HiFIGAN", savedir="tmpdir")
+ mel_specs = torch.rand(2, 80,298)
+ waveforms = hifi_gan.decode_batch(mel_specs)
+```
+### Using the Vocoder with the TTS
+```
+import torchaudio
+from speechbrain.pretrained import Tacotron2
+from speechbrain.pretrained import HIFIGAN
+
+# Intialize TTS (tacotron2) and Vocoder (HiFIGAN)
+tacotron2 = Tacotron2.from_hparams(source="speechbrain/TTS_Tacotron2", savedir="tmpdir_tts")
+hifi_gan = HIFIGAN.from_hparams(source="speechbrain/Vocoder_HiFIGAN", savedir="tmpdir_vocoder")
+
+# Running the TTS
+mel_output, mel_length, alignment = tacotron2.encode_text("Mary had a little lamb")
+
+# Running Vocoder (spectrogram-to-waveform)
+waveforms = hifi_gan.decode_batch(mel_output)
+
+# Save the waverform
+torchaudio.save('example_TTS.wav',waveforms.squeeze(1), 22050)
+```
+
+### Inference on GPU
+To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.
+
+### Training
+The model was trained with SpeechBrain.
+To train it from scratch follow these steps:
+1. Clone SpeechBrain:
+```bash
+git clone https://github.com/speechbrain/speechbrain/
+```
+2. Install it:
+```bash
+cd speechbrain
+pip install -r requirements.txt
+pip install -e .
+```
+3. Run Training:
+```bash
+cd recipes/LJSpeech/TTS/vocoder/hifi_gan/
+python train.py hparams/train.yaml --data_folder /path/to/LJspeech
 ```
+You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/19sLwV7nAsnUuLkoTu5vafURA9Fo2WZgG?usp=sharing).