mirror of https://github.com/coqui-ai/TTS.git
8be21ec387
* new CI config * initial Capacitron implementation * delete old unused file * fix empty formatting changes * update losses and training script * fix previous commit * fix commit * Add Capacitron test and first round of test fixes * revert formatter change * add changes to the synthesizer * add stepwise gradual lr scheduler and changes to the recipe * add inference script for dev use * feat: add posterior inference arguments to synth methods - added reference wav and text args for posterior inference - some formatting * fix: add espeak flag to base_tts and dataset APIs - use_espeak_phonemes flag was not implemented in those APIs - espeak is now able to be utilised for phoneme generation - necessary phonemizer for the Capacitron model * chore: update training script and style - training script includes the espeak flag and other hyperparams - made style * chore: fix linting * feat: add Tacotron 2 support * leftover from dev * chore:rename parser args * feat: extract optimizers - created a separate optimizer class to merge the two optimizers * chore: revert arbitrary trainer changes * fmt: revert formatting bug * formatting again * formatting fixed * fix: log func * fix: update optimizer - Implemented load_state_dict for continuing training * fix: clean optimizer init for standard models * improvement: purge espeak flags and add training scripts * Delete capacitronT2.py delete old training script, new one is pushed * feat: capacitron trainer methods - extracted capacitron specific training operations from the trainer into custom methods in taco1 and taco2 models * chore: renaming and merging capacitron and gst style args * fix: bug fixes from the previous commit * fix: implement state_dict method on CapacitronOptimizer * fix: call method * fix: inference naming * Delete train_capacitron.py * fix: synthesize * feat: update tests * chore: fix style * Delete capacitron_inference.py * fix: fix train tts t2 capacitron tests * fix: double forward in T2 train step * fix: double forward in T1 train step * fix: run make style * fix: remove unused import * fix: test for T1 capacitron * fix: make lint * feat: add blizzard2013 recipes * make style * fix: update recipes * chore: make style * Plot test sentences in Tacotron * chore: make style and fix import * fix: call forward first before problematic floordiv op * fix: update recipes * feat: add min_audio_len to recipes * aux_input["style_mel"] * chore: make style * Make capacitron T2 recipe more stable * Remove T1 capacitron Ljspeech * feat: implement new grad clipping routine and update configs * make style * Add pretrained checkpoints * Add default vocoder * Change trainer package * Fix grad clip issue for tacotron * Fix scheduler issue with tacotron Co-authored-by: Eren Gölge <egolge@coqui.ai> Co-authored-by: WeberJulian <julian.weber@hotmail.fr> Co-authored-by: Eren Gölge <erogol@hotmail.com> |
||
|---|---|---|
| .. | ||
| align_tts | ||
| fast_pitch | ||
| fast_speech | ||
| glow_tts | ||
| hifigan | ||
| multiband_melgan | ||
| speedy_speech | ||
| tacotron2-Capacitron | ||
| tacotron2-DCA | ||
| tacotron2-DDC | ||
| univnet | ||
| vits_tts | ||
| wavegrad | ||
| wavernn | ||
| README.md | ||
| download_ljspeech.sh | ||
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.pyRunning 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 💪.