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Unoffical implementation of Megatts2
| Date | Stars |
|---|---|
| 2026-07-24 | 285 |
| 2026-07-25 | 285 |
| 2026-07-28 | 285 |
| 2026-07-30 | 285 |
| 2026-08-06 | 285 |
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# megatts2
Unofficial implementation of Megatts2
## TODO
### Base test
- [x] Prepare dataset
- [x] VQ-GAN
- [x] ADM
- [x] PLM
### Better version
- [ ] Replace Hifigan with Bigvgan
- [ ] Mix training Chinese and English
- [ ] Train on about 1k hours of speech
- [ ] Webui
## Install mfa
1. conda create -n aligner && conda activate aligner
2. conda install -c conda-forge montreal-forced-aligner=2.2.17
## Prepare dataset
1. Prepare wav and txt files to ./data/wav
2. Run `python3 prepare_ds.py --stage 0 --num_workers 4 --wavtxt_path data/wavs --text_grid_path data/textgrids --ds_path data/ds`
3. mfa model download acoustic mandarin_mfa
4. mfa align data/wavs utils/mandarin_pinyin_to_mfa_lty.dict mandarin_mfa data/textgrids --clean -j 12 -t /workspace/tmp
5. Run `python3 prepare_ds.py --stage 1 --num_workers 4 --wavtxt_path data/wavs --text_grid_path data/textgrids --ds_path data/ds`
6. Run `python3 prepare_ds.py --stage 2 --generator_config configs/config_gan.yaml --generator_ckpt generator.ckpt` after training generator.
## Train
Training procedure refers to Pytorch-lightning
## Infer test
`python infer.py`
## Citing
```bibtex
@misc{2307.07218,
Author = {Ziyue Jiang and Jinglin Liu and Yi Ren and Jinzheng He and Chen Zhang and Zhenhui Ye and Pengfei Wei and Chunfeng Wang and Xiang Yin and Zejun Ma and Zhou Zhao},
Title = {Mega-TTS 2: Zero-Shot Text-to-Speech with Arbitrary Length Speech Prompts},
Year = {2023},
Eprint = {arXiv:2307.07218},
}
```
## License
- MIT
- Support by Simon of [ZideAI](https://zideai.com/)Excerpt of 1,543 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:93b0880199c2921e, topic:tts, readme:text-to-speech