license: mit
datasets:
- mozilla-foundation/common_voice_16_0
language:
- be
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