TTS Project

Based on this template and this FastSpeech 1 implementation.

Installation guide

pip install -r ./requirements.txt
wget https://github.com/xcmyz/FastSpeech/raw/master/alignments.zip
unzip alignments.zip >> /dev/null
mkdir data ; mkdir data/datasets ; mkdir data/datasets/ljspeech
mv alignments data/datasets/ljspeech/alignments

gdown https://drive.google.com/u/0/uc?id=1cJKJTmYd905a-9GFoo5gKjzhKjUVj83j
tar -xvf mel.tar.gz
echo $(ls mels | wc -l)

mv mels data/datasets/ljspeech

python3 preprocess.py

gdown https://drive.google.com/u/0/uc?id=1WsibBTsuRg_SF2Z6L6NFRTT-NjEy1oTx
mkdir -p waveglow/pretrained_model/
mv waveglow_256channels_ljs_v2.pt waveglow/pretrained_model/waveglow_256channels.pt

gdown https://drive.google.com/file/d/14CCYsCJlaQ5KUdY8vw6_xxbvx1ZuSQzw/view?usp=sharing -O default_test_model/checkpoint.pth --fuzzy

Usage guide

To train:

python3 train.py --config-name fastspeech2

To synthesize audio:

python3 train.py --config-name inference_fs2 +trainer.checkpoint_path=default_test_model/checkpoint.pth

Feel free to change tts/config/inference_fs2.yaml to set texts & alphas for synthesis. Alternatively, you can use Hydra CLI features.