(A fork of) a multi-voice TTS system trained with an emphasis on quality
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| tortoise_tts | ||
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| README.md | ||
| setup.py | ||
TorToiSe TTS
An unofficial PyTorch re-implementation of TorToise TTS.
Requirements
A working PyTorch environment.
Install
Simply run pip install git+https://git.ecker.tech/mrq/tortoise-tts or pip install git+https://github.com/e-c-k-e-r/tortoise-tts.
To-Do
- Reimplement original inferencing through TorToiSe (as done with
api.py) - Implement training support (without DLAS)
- Feature parity with the VALL-E training setup with preparing a dataset ahead of time
- Automagic handling of the original weights into compatible weights
- Extend the original inference routine with additional features:
- non-float32 / mixed precision
- BitsAndBytes support
- LoRAs
- Web UI
- Feature parity with ai-voice-cloning
- Additional samplers for the autoregressive model
- Additional samplers for the diffusion model
- BigVGAN in place of the original vocoder
- XFormers / flash_attention_2 for the autoregressive model
- Some vector embedding store to find the "best" utterance to pick
Why?
To correct the mess I've made with forking TorToiSe TTS originally with a bunch of slopcode, and the nightmare that ai-voice-cloning turned out.
Additional features can be applied to the program through a framework of my own that I'm very familiar with.
License
Unless otherwise credited/noted in this README or within the designated Python file, this repository is licensed under AGPLv3.