A simple utility for synthesizing English speech from the command line; uses NVIDIA's Tacotron2 and WaveGlow models to do the work, both of which were trained using the LJ Speech dataset. Just a quick little thing that we thought was neat.
Some of the code is taken directly from NVIDIA's TorchHub example (see links).
Please note that this is not a maintained project. Additionally, it also no longer represents state-of-the-art; while I haven't taken the time to investigate the following, it may be of interest:
MelGAN Vocoder code, and paper.
- NVIDIA's WaveGlow example
- Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
- WaveGlow: A Flow-based Generative Network for Speech Synthesis
Decent: knuth.wav
Really bad: shakespeare.wav
You can pip install -r DEPENDENCIES to get these.
- torch
- matplotlib
- numpy
- inflect
- librosa
- scipy
- unidecode
- plac
With a GTX 1080 Ti video card and an Intel Core i7-7700k (4.2GHz), it takes roughly a second per word or two.
The LJ Speech dataset is public domain and NVIDIA's models are covered by a BSD 3-clause license. Imagine the court battles Hollywood is going to go through when we really get these things right.