Light Speed ⚡

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.

Pretrained models and demos

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

FAQ

Q: How do I train on custom dataset?
A: See the ./prepare_audio_1_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 --tfdata tfdata --rm-old-ckpt > logs/run.log

Q: How can I train the model with specific GPU? A: Run: CUDA_VISIBLE_DEVICES=2,3 torchrun --standalone --nnodes=1 --nproc-per-node=2 train.py --tfdata tfdata --rm-old-ckpt --batch-size 16

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.

Credits

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

fix bug

• bug with mfa aligner use newer version of mfa see here
• bug with vbx dataset install git lfs

  curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash sudo apt-get install git-lfs

• when train with custom dataset txt file and wav must be in the same folder
• need to train separate duration model when inference
• run mfa train -h to see how to config train ( it train on CPU don't know why)
• to view loss table with tensorboard
  • ctrl + shift + p -> python:Launch Tensorboard -> choose logs folder