Skip to content
A Pytorch implementation of WaveVAE ("Parallel Neural Text-to-Speech")
Python
Branch: master
Clone or download
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
LICENSE Create LICENSE May 23, 2019
README.md Update README.md May 23, 2019
data.py First commit May 23, 2019
model.py First commit May 23, 2019
modules.py correct a mistake in STFT loss May 23, 2019
preprocessing.py First commit May 23, 2019
synthesize.py minor errors May 23, 2019
train.py annealing coeff correction May 23, 2019
wavenet.py First commit May 23, 2019
wavenet_iaf.py First commit May 23, 2019

README.md

WaveVAE

work in progress

Note that my implementation isn't stable yet.

A Pytorch Implementation of WaveVAE (Mel Spectrogram --> Waveform)

part of "Parallel Neural Text-to-Speech"

Requirements

PyTorch 0.4.1 & python 3.6 & Librosa

Examples

Step 1. Download Dataset

Step 2. Preprocessing (Preparing Mel Spectrogram)

python preprocessing.py --in_dir ljspeech --out_dir DATASETS/ljspeech

Step 3. Train Model

python train.py --model_name wavevae_1 --batch_size 4 --num_gpu 2

Step 4. Synthesize

--load_step CHECKPOINT : the # of the model's global training step (also depicted in the trained weight file)

python synthesize.py --model_name wavevae_1 --load_step 10000 --num_samples 5

References

You can’t perform that action at this time.