mirror of https://github.com/coqui-ai/TTS.git
* Fix checkpointing GAN models (#1641)
* checkpoint sae step crash fix
* checkpoint save step crash fix
* Update gan.py
updated requested changes
* crash fix
* Fix the --model_name and --vocoder_name arguments need a <model_type> element (#1469)
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Fix Publish CI (#1597)
* Try out manylinux
* temporary removal of useless pipeline
* remove check and use only manylinux
* Try --plat-name
* Add install requirements
* Add back other actions
* Add PR trigger
* Remove conditions
* Fix sythax
* Roll back some changes
* Add other python versions
* Add test pypi upload
* Add username
* Add back __token__ as username
* Modify name of entry to testpypi
* Set it to release only
* Fix version checking
* Fix tokenizer for punc only (#1717)
* Remove redundant config field
* Fix SSIM loss
* Separate loss tests
* Fix BCELoss adressing #1192
* Make style
* Add durations as aux input for VITS (#1694)
* Add durations as aux input for VITS
* Make style
* Fix tts_tests
* Fix test_get_aux_input
* Make lint
* feat: updated recipes and lr fix (#1718)
- updated the recipes activating more losses for more stable training
- re-enabling guided attention loss
- fixed a bug about not the correct lr fetched for logging
* Implement VitsAudioConfig (#1556)
* Implement VitsAudioConfig
* Update VITS LJSpeech recipe
* Update VITS VCTK recipe
* Make style
* Add missing decorator
* Add missing param
* Make style
* Update recipes
* Fix test
* Bug fix
* Exclude tests folder
* Make linter
* Make style
* Fix device allocation
* Fix SSIM loss correction
* Fix aux tests (#1753)
* Set n_jobs to 1 for resample script
* Delete resample test
* Set n_jobs 1 in vad test
* delete vad test
* Revert "Delete resample test"
This reverts commit
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blizzard2013 | ||
kokoro/tacotron2-DDC | ||
ljspeech | ||
multilingual/vits_tts | ||
thorsten_DE | ||
vctk | ||
README.md |
README.md
🐸💬 TTS Training Recipes
TTS recipes intended to host scripts running all the necessary steps to train a TTS model on a particular dataset.
For each dataset, you need to download the dataset once. Then you run the training for the model you want.
Run each script from the root TTS folder as follows.
$ sh ./recipes/<dataset>/download_<dataset>.sh
$ python recipes/<dataset>/<model_name>/train.py
For some datasets you might need to resample the audio files. For example, VCTK dataset can be resampled to 22050Hz as follows.
python TTS/bin/resample.py --input_dir recipes/vctk/VCTK/wav48_silence_trimmed --output_sr 22050 --output_dir recipes/vctk/VCTK/wav48_silence_trimmed --n_jobs 8 --file_ext flac
If you train a new model using TTS, feel free to share your training to expand the list of recipes.
You can also open a new discussion and share your progress with the 🐸 community.