History

Shivam Mehta d83ee8fe45 Adding neural HMM TTS Model (#2272 ) * Adding neural HMM TTS * Adding tests * Adding neural hmm on readme * renaming training recipe * Removing overflow\s decoder parameters from the config * Update the Trainer requirement version for a compatible one (#2276) * Bump up to v0.10.2 * Adding neural HMM TTS * Adding tests * Adding neural hmm on readme * renaming training recipe * Removing overflow\s decoder parameters from the config * fixing documentation Co-authored-by: Edresson Casanova <edresson1@gmail.com> Co-authored-by: Eren Gölge <erogol@hotmail.com>		2023-01-23 11:53:04 +01:00
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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	Adding neural HMM TTS Model (#2272 )	2023-01-23 11:53:04 +01:00
multilingual/vits_tts	Multilingual tokenizer (#2229 )	2023-01-02 10:03:19 +01:00
thorsten_DE	d-vector handling (#1945 )	2022-09-13 14:10:33 +02:00
vctk	Fixed bug related to yourtts speaker embeddings issue (#2234 )	2023-01-02 14:20:02 +01:00
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.