Pytorch implementation of DeepMind's WaveNet utilizing PyTorch
by: Jacqueline Abalo and John Donaghy
pytorch, torchvision, numpy, matplotlib, scipy
Dynamically built Wavenet model entirely described using command-line arguments. Driven by train.py with model definitions in model.py and data handling in data.py.
Data.py houses functionality to load LJSpeech dataset and VCTK dataset.
Also made available is functionality to load Partita for Violin No. 2 by Johann Sebastian Bach, credit: Vincent Herrmann.
MuLawExpanding and MuLawDecoding in transforms.py credit: Sungwon Kim
python train.py --dataset [dataset] --data_path [path/to/dataset/] --epochs [# epochs] --batch_size [# samples per batch] --use_cuda True
python train.py --help