TFGAN
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TFGAN: Time and Frequency Domain Based Generative Adversarial Network for High-fidelity Speech Synthesis
TFGAN
This repo is Unofficial implements of TFGAN: Time and Frequency Domain Based Generative Adversarial Network for High-fidelity Speech Synthesis using Pytorch.
Requirement
Tested on Python 3.6
pip install -r requirements.txt
Prepare Dataset
- Download dataset for training. This can be any wav files with sample rate 22050Hz. (e.g. LJSpeech was used in paper)
- preprocess:
python preprocess.py -c config/default.yaml -d [data's root path]
- Edit configuration
yaml
file
Train & Tensorboard
-
python trainer.py -c [config yaml file] -n [name of the run]
-
cp config/default.yaml config/config.yaml
and then editconfig.yaml
- Write down the root path of train/validation files to 2nd/3rd line.
-
-
tensorboard --logdir logs/
Inference
-
python inference.py -p [checkpoint path] -i [input mel path]
Checkpoint :
- LJSpeech checkpoint here .