GAN-TTS

A pytorch implementation of the GAN-TTS: HIGH FIDELITY SPEECH SYNTHESIS WITH ADVERSARIAL NETWORKS(https://arxiv.org/pdf/1909.11646.pdf)

Prepare dataset

• Download dataset for training. This can be any wav files with sample rate 24000Hz.
• Process: python process.py --wav_dir="wavs" --output="data"
• Edit configuration in utils/audio.py

Train & Tensorboard

• python train.py --input="data/train"
• tensorboard --logdir logdir

Inference

• python generate.py --input="data/test"

Attention

• I did not use the loss function mentioned in the paper. I modified the loss function and learn from ParallelWaveGAN(https://arxiv.org/pdf/1910.11480.pdf).

Notes

• This is not official implementation, some details are not necessarily correct.
• The current results still have some noise, I suspect it is caused by the size of the batch.
• Work in progress.