mirror of https://github.com/coqui-ai/TTS.git
fix typos
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@ -21,7 +21,7 @@ them and fine-tune it for your own dataset. This will help you in two main ways:
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Fine-tuning comes to the rescue in this case. You can take one of our pre-trained models and fine-tune it on your own
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speech dataset and achieve reasonable results with only a couple of hours of data.
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However, note that, fine-tuning does not ensure great results. The model performance is still depends on the
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However, note that, fine-tuning does not ensure great results. The model performance still depends on the
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{ref}`dataset quality <what_makes_a_good_dataset>` and the hyper-parameters you choose for fine-tuning. Therefore,
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it still takes a bit of tinkering.
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@ -41,7 +41,7 @@ them and fine-tune it for your own dataset. This will help you in two main ways:
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tts --list_models
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```
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The command above lists the the models in a naming format as ```<model_type>/<language>/<dataset>/<model_name>```.
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The command above lists the models in a naming format as ```<model_type>/<language>/<dataset>/<model_name>```.
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Or you can manually check the `.model.json` file in the project directory.
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