coqui-ai
/
TTS
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
TTS/recipes/ljspeech
History
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
README.md Create LJSpeech recipes for all the models 2021-06-22 16:21:11 +02:00
download_ljspeech.sh Fix ljspeech download 2021-10-25 11:33:51 +02:00

README.md

🐸💬 TTS LJspeech Recipes

For running the recipes

  1. Download the LJSpeech dataset here either manually from its official website or using download_ljspeech.sh.

  2. 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 💪.