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prakharpbuf c1875f68df
typos and minor fixes (#2508) 
* Update tacotron1-2.md

* Update README.md

* Update Tutorial_2_train_your_first_TTS_model.ipynb

* Update synthesizer.py

There is no arg called --speaker_name

* Update formatting_your_dataset.md

* Update AnalyzeDataset.ipynb

* Update AnalyzeDataset.ipynb

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* Update finetuning.md

* Update train_yourtts.py

* Update train_yourtts.py

* Update train_yourtts.py

* Update finetuning.md
 		2023-04-26 15:22:57 +02:00
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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 typos and minor fixes (#2508) 2023-04-26 15:22:57 +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.