mrq/tortoise-tts
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James Betker 2022-03-10 23:33:48 -07:00
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@ -51,15 +51,14 @@ python do_tts.py
I generated ~250 samples from 23 text prompts and 8 voices. The text prompts have never been seen by the model. The I generated ~250 samples from 23 text prompts and 8 voices. The text prompts have never been seen by the model. The
voices were pulled from the training set. voices were pulled from the training set.
All of the samples can be found in the results/ folder of this repo. All of the samples can be found in the results/ folder of this repo. I handpicked a few to show what the model is capable of:
I handpicked a few to show what the model is capable of: - [Atkins - Road not taken](results/favorites/atkins_road_not_taken.wav)
[Atkins - Road not taken](results/favorites/atkins_road_not_taken.wav) - [Dotrice - Rolling Stone interview](results/favorites/dotrice_rollingstone.wav)
[Dotrice - Rolling Stone interview](results/favorites/dotrice_rollingstone.wav) - [Dotrice - 'Ornaments' from tacotron test set](results/favorites/dotrice_tacotron_samp1.wav)
[Dotrice - 'Ornaments' from tacotron test set](results/favorites/dotrice_tacotron_samp1.wav) - [Kennard - 'Acute emotional intelligence' from tacotron test set](results/favorites/kennard_tacotron_samp2.wav)
[Kennard - 'Acute emotional intelligence' from tacotron test set](results/favorites/kennard_tacotron_samp2.wav) - [Mol - Because I could not stop for death](results/favorites/mol_dickenson.wav)
[Mol - Because I could not stop for death](results/favorites/mol_dickenson.wav) - [Mol - Obama](results/favorites/mol_obama.wav)
[Mol - Obama](results/favorites/mol_obama.wav)
Prosody is remarkably good for poetry, despite the fact that it was never trained on poetry. Prosody is remarkably good for poetry, despite the fact that it was never trained on poetry.