mirror of https://github.com/wassname/TTS.git synced 2026-09-18 12:10:08 +08:00

Files

T

Eren Gölge 035ed432bc Doc update (#889 )

* Link source files from the docs

* Update glowTTS recipes for docs

* Add dataset downloaders

2021-10-26 17:41:33 +02:00

align_tts

VCTK recipes (finally 🚀)

2021-10-21 16:29:06 +00:00

fast_pitch

VCTK recipes (finally 🚀)

2021-10-21 16:29:06 +00:00

fast_speech

VCTK recipes (finally 🚀)

2021-10-21 16:29:06 +00:00

glow_tts

Doc update (#889 )

2021-10-26 17:41:33 +02:00

hifigan

Update GAN for Trainer_v2

2021-09-30 14:47:56 +00:00

multiband_melgan

Update GAN for Trainer_v2

2021-09-30 14:47:56 +00:00

speedy_speech

VCTK recipes (finally 🚀)

2021-10-21 16:29:06 +00:00

tacotron2-DCA

Fix import statements

2021-10-25 19:29:16 +02:00

tacotron2-DDC

Fix import statements

2021-10-25 19:29:16 +02:00

univnet

Fix imports

2021-09-30 14:47:56 +00:00

vits_tts

Fix import statements

2021-10-25 19:29:16 +02:00

wavegrad

Fix imports

2021-09-30 14:47:56 +00:00

wavernn

Fix imports

2021-09-30 14:47:56 +00:00

download_ljspeech.sh

Fix ljspeech download

2021-10-25 11:33:51 +02:00

README.md

Create LJSpeech recipes for all the models

2021-06-22 16:21:11 +02:00

README.md

🐸💬 TTS LJspeech Recipes

For running the recipes

Download the LJSpeech dataset here either manually from its official website or using download_ljspeech.sh.
Go to your desired model folder and run the training.

Running Python files. (Choose the desired GPU ID for your run and set CUDA_VISIBLE_DEVICES)
```
CUDA_VISIBLE_DEVICES="0" python train_modelX.py
```
Running bash scripts.
```
bash run.sh
```

💡 Note that these runs are just templates to help you start training your first model. They are not optimized for the best result. Double-check the configurations and feel free to share your experiments to find better parameters together 💪.