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Eren Gölge 9e5a469c64
d-vector handling (#1945) 
* Update BaseDatasetConfig

- Add dataset_name
- Chane name to formatter_name

* Update compute_embedding

- Allow entering dataset by args
- Use released model by default
- Use the new key format

* Update loading

* Update recipes

* Update other dep code

* Update tests

* Fixup

* Load multiple embedding files

* Fix argument names in dep code

* Update docs

* Fix argument name

* Fix linter
 		2022-09-13 14:10:33 +02:00
..
blizzard2013 d-vector handling (#1945) 2022-09-13 14:10:33 +02:00
kokoro/tacotron2-DDC d-vector handling (#1945) 2022-09-13 14:10:33 +02:00
ljspeech d-vector handling (#1945) 2022-09-13 14:10:33 +02:00
multilingual/vits_tts d-vector handling (#1945) 2022-09-13 14:10:33 +02:00
thorsten_DE d-vector handling (#1945) 2022-09-13 14:10:33 +02:00
vctk d-vector handling (#1945) 2022-09-13 14:10:33 +02:00
README.md Update recipes README.md 2022-02-25 11:16:30 +01:00

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.