metadata

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 vocoder trained with LibriTTS (with multiple speakers). The sample rate used for the vocoder is 16000 Hz.

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.

Alternatives to this models are the following:

tts-hifigan-libritts-22050Hz (same model trained on the same dataset, but for a sample rate of 22050 Hz)
tts-hifigan-ljspeech (same model trained on LJSpeech for a sample rate of 22050 Hz).

Install SpeechBrain

pip install speechbrain

Please notice that we encourage you to read our tutorials and learn more about SpeechBrain.

Using the Vocoder

import torch
from speechbrain.pretrained import HIFIGAN
hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-libritts-16kHz", savedir="tmpdir")
mel_specs = torch.rand(2, 80,298)

# Running Vocoder (spectrogram-to-waveform)
waveforms = hifi_gan.decode_batch(mel_specs)

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:

Clone SpeechBrain:

git clone https://github.com/speechbrain/speechbrain/

Install it:

cd speechbrain
pip install -r requirements.txt
pip install -e .

Run Training:

cd recipes/LibriTTS/vocoder/hifigan/
python train.py hparams/train.yaml --data_folder=/path/to/LibriTTS_data_destination --sample_rate=16000

To change the sample rate for model training go to the "recipes/LibriTTS/vocoder/hifigan/hparams/train.yaml" file and change the value for sample_rate as required. The training logs and checkpoints are available here.