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