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slapula/commonvoice_be_tts_female_1
commonvoice_be_tts_female_1 is a machine learning model from slapula. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
This is my first attempt at training a Belarusian voice using Coqui TTS and Mozilla's CommonVoice dataset. This model was developed based on the excellent recipe provided by bel-alex73. For this particular model, I tw…
Downloads · 30 days
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.pth1.4 GB · 100%
From the Hugging Face model README
This is my first attempt at training a Belarusian voice using Coqui TTS and Mozilla's CommonVoice dataset. This model was developed based on the excellent recipe provided by bel-alex73. For this particular model, I tweaked the search results to find single speakers with over 30 hours of audio and selected speakers based on clarity and relatively slow speaking cadence. This was a manual selection process that involved me tweaking bel-alex73 choose_speaker.ipynb notebook to show/process more that just the top ranked speaker.
This model is generated from the following client_id: 216de8fc1b7973a11926dd6694d2a97c3ceaf5a626ec4c8d2c85c8140a10ec5ed59bd6ee756c8c3451ee0cf784e4af445748cd69a2936102489b95f3409cd0d7
I am not a native speaker of Belarusian and I am doing this to assist in my language learning efforts. I am open to any and all feedback (esp. from native speakers) so feel free to post questions/comments.
Input text needs to be phoneme-ized in order for this model to process the speech correctly. This process has been documented in bel-alex73's README.
tts --text "<phonemes>" --out_path output.wav \
--config_path config.json \
--model_path best_model.pth \
--vocoder_config_path vocoder_config.json \
--vocoder_path vocoder_best_model.pth