Medix-AI/coqui-tts
Medix-AI
/
coqui-tts
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
coqui-tts/recipes/ljspeech
History
Eren Gölge 1c3623af33
Fix model manager (#1436) 
* Fix manager

* Make style
 		2022-03-23 12:57:14 +01:00
..
align_tts Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
fast_pitch Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
fast_speech Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
glow_tts Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
hifigan Make style (#1405) 2022-03-16 12:13:55 +01:00
multiband_melgan Make style (#1405) 2022-03-16 12:13:55 +01:00
speedy_speech Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
tacotron2-DCA Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
tacotron2-DDC Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
univnet Make style (#1405) 2022-03-16 12:13:55 +01:00
vits_tts Fix model manager (#1436) 2022-03-23 12:57:14 +01:00
wavegrad Make style 2022-02-25 11:26:59 +01:00
wavernn Make style 2022-02-25 11:26:59 +01:00
README.md Create LJSpeech recipes for all the models 2021-06-22 16:21:11 +02:00
download_ljspeech.sh Update ljspeech download 2022-02-25 11:12:44 +01:00

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 💪.