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@@ -7,22 +7,24 @@ tags:
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  - Text-to-Speech
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  datasets:
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  - CMU Arctic
 
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  ---
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  # TTS Models
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  Here you can find models compatible with
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- [balacoon_tts](https://pypi.org/project/balacoon_tts/) python package.
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  You can check interactive demo and models usage example in
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  [balacoon/tts](https://huggingface.co/spaces/balacoon/tts) space.
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  List of available models:
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  - <mark>en_us_cmuarctic_pt_univenet.addon</mark> - en-US TTS trained on all 18
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- [CMU Arctic](http://festvox.org/cmu_arctic/) voices. This includes
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- examples of absolutely dashing accents, with "slp" voice being my
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- personal absolute favorite. Model consists of
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- [Parallel Tacotron](https://arxiv.org/abs/2010.11439)
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- and pre-trained [Univnet](https://github.com/mindslab-ai/univnet).
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- Model produces 24khz audio, although original dataset is unfortunately
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- 16khz, so high frequencies are empty :(
 
 
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  - Text-to-Speech
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  datasets:
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  - CMU Arctic
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+ - Hi-Fi
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  ---
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  # TTS Models
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  Here you can find models compatible with
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+ [balacoon_tts](https://balacoon.com) python package.
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  You can check interactive demo and models usage example in
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  [balacoon/tts](https://huggingface.co/spaces/balacoon/tts) space.
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  List of available models:
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  - <mark>en_us_cmuarctic_pt_univenet.addon</mark> - en-US TTS trained on all 18
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+ [CMU Arctic](http://festvox.org/cmu_arctic/) voices.
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+ - <mark>en_us_hifi92_pt_univenet.addon</mark> - en-US TTS trained on
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+ a single clean speaker(92) from [Hi-Fi dataset](https://arxiv.org/abs/2104.01497).
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+
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+ Model names hints architecture used:
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+
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+ - `pt_univenet` - combination of [Parallel Tacotron](https://arxiv.org/abs/2010.11439)
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+ and pre-trained [Univnet](https://github.com/mindslab-ai/univnet).