Light Speed ⚡ is an open-source text-to-speech model based on VITS, with some modifications:

• utilizes phoneme duration's ground truth, obtained from an external forced aligner (such as Montreal Forced Aligner), to upsample phoneme information to frame-level information. The result is a more robust model, with a slight trade-off in speech quality.
• employs dilated convolution to expand the Wavenet Flow module's receptive field, enhancing its ability to capture long-range interactions.

We provide two pretrained models and demos:

• VN - Male voice: https://huggingface.co/spaces/ntt123/Vietnam-male-voice-TTS
• VN - Female voice: https://huggingface.co/spaces/ntt123/Vietnam-female-voice-TTS

Q: How do I create training data?
A: See the ./prepare_ljs_tfdata.ipynb notebook for instructions on preparing the training data.

Q: How can I train the model with 1 GPU?
A: Run: python train.py

Q: How can I train the model with 4 GPUs?
A: Run: torchrun --standalone --nnodes=1 --nproc-per-node=4 train.py

Q: How can I train a model to predict phoneme durations?
A: See the ./train_duration_model.ipynb notebook.

Q: How can I generate speech with a trained model?
A: See the ./inference.ipynb notebook.

• Most of the code in this repository is based on the VITS official repository.