PyTorch
Catalan
TTS
audio
synthesis
VITS
speech
coqui.ai
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openslr added to README

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  datasets:
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  - mozilla-foundation/common_voice_8_0
 
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  ---
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  # Aina Project's Catalan multi-speaker text-to-speech model
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  ## Model description
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- This model was trained from scratch using the [Coqui TTS](https://github.com/coqui-ai/TTS) toolkit on a combination of 3 datasets: [Festcat](http://festcat.talp.cat/devel.php), high quality open speech dataset of [Google](http://openslr.org/69/) and [Common Voice v8](https://commonvoice.mozilla.org/ca). For the training, 101460 utterances consisting of 257 speakers were used, which corresponds to nearly 138 hours of speech.
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  A live inference demo can be found in our spaces, [here](https://huggingface.co/spaces/projecte-aina/tts-ca-coqui-vits-multispeaker).
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  datasets:
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  - mozilla-foundation/common_voice_8_0
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+ - openslr
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  ---
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  # Aina Project's Catalan multi-speaker text-to-speech model
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  ## Model description
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+ This model was trained from scratch using the [Coqui TTS](https://github.com/coqui-ai/TTS) toolkit on a combination of 3 datasets: [Festcat](http://festcat.talp.cat/devel.php), high quality open speech dataset of [Google](http://openslr.org/69/) (can be found in [OpenSLR 69](https://huggingface.co/datasets/openslr/viewer/SLR69/train)) and [Common Voice v8](https://commonvoice.mozilla.org/ca). For the training, 101460 utterances consisting of 257 speakers were used, which corresponds to nearly 138 hours of speech.
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  A live inference demo can be found in our spaces, [here](https://huggingface.co/spaces/projecte-aina/tts-ca-coqui-vits-multispeaker).
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