Create README.md

README.md

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+---
+language: "en"
+inference: false
+tags:
+- Vocoder
+- HiFIGAN
+- text-to-speech
+- TTS
+- speech-synthesis
+- speechbrain
+license: "apache-2.0"
+datasets:
+- LibriTTS
+---
+
+# Vocoder with HiFIGAN trained on LibriTTS
+
+This repository provides all the necessary tools for using a [HiFIGAN](https://arxiv.org/abs/2010.05646) vocoder trained with [LibriTTS](https://www.openslr.org/60/). The sample rate used for the vocoder is 22050 kHz.
+
+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
+
+```bash
+pip install speechbrain
+```
+
+
+Please notice that we encourage you to read our tutorials and learn more about
+[SpeechBrain](https://speechbrain.github.io).
+
+### Using the Vocoder
+
+```python
+import torch
+from speechbrain.pretrained import HIFIGAN
+hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-libritts-22050Hz", savedir="tmpdir")
+mel_specs = torch.rand(2, 80,298)
+
+# Running Vocoder (spectrogram-to-waveform)
+waveforms = hifi_gan.decode_batch(mel_specs)
+
+# Save the waveform
+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/LibriTTS/vocoder/hifigan/
+python train.py hparams/train.yaml --data_folder=/path/to/LibriTTS_data_destination
+```
+
+To change the sample rate for model training go to the `"vocoder/hifigan/hparams/train.yaml"` file and change the value for `sample_rate` as required.