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GlowTTS + HifiGAN Male Belarusian Voice #1

This is my third 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: 235555b6d6c6b4d882a5a0e6160f245c03e61d266c112dc3cecaeb7bcf9802d70be375ffaf9590dd7b24e95284ce06ee295da529cebd9c67f29db31cb8f092cb

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.

Sythesizing text to speech

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
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Dataset used to train slapula/commonvoice_be_tts_male_1