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"
PyTorch 0.4.1 & python 3.6 & Librosa
- LJSpeech : https://keithito.com/LJ-Speech-Dataset/
python preprocessing.py --in_dir ljspeech --out_dir DATASETS/ljspeech
python train.py --model_name wavevae_1 --batch_size 4 --num_gpu 2
--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
- WaveNet vocoder : https://github.com/r9y9/wavenet_vocoder
- Parallel Neural Text-to-Speech : https://arxiv.org/abs/1905.08459