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.

Prerequisites

• 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

Usage

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

Results

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

Author

Hyungcheol Noh / About Me

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