WaveNet Implementation in TensorFlow
This repository is for a TensorFlow implementation of Google’s WaveNet. The original link of WaveNet paper is here. In this repository, only global conditioning was implemented for WaveNet model.
- Python 3.5
- librosa 0.6.2 or higher
- numpy 1.14.5 or higher
- tensorflow-gpu 1.10.0 or higher
More simpler way to install these prerequisites using python 3.5 virtualenv is that:
>>> virtualenv --system-site-packages -p python3 wavenet-venv >>> source ./wavenet-venv/bin/activate >>> pip install -r requirements.txt
The dataset directory should be organized by this structure.
dataset ├── p01 (person name, the name doesn't matter) ├── txt ├── xxx.txt (name doesn't matter) ├── yyy.txt └── ... └── wav ├── xxx.wav (name doesn't matter but should be same with corresponding txt file) ├── yyy.wav └── ... ├── p02 └── ...
To train a model:
>>> python train.py
Also, to generate a audio with a trained model:
>>> python generate.py
I trained WaveNet model without using any global conditions. The trained model just mimics voice from original audio dataset.
- The original audio sample that I used as a dataset: https://soundcloud.com/artzizou/p280-original-sample?in=artzizou/sets/wavenet-tensorflow
- A generated audio from my trained WaveNet model: https://soundcloud.com/artzizou/p280-final-version?in=artzizou/sets/wavenet-tensorflow
Hyungcheol Noh / About Me