Phonetically rich corpus construction for a low-resourced language
<|reference_start|>Phonetically rich corpus construction for a low-resourced language: Speech technologies rely on capturing a speaker's voice variability while obtaining comprehensive language information. Textual prompts and sentence selection methods have been proposed in the literature to comprise such adequate phonetic data, referred to as a phonetically rich \textit{corpus}. However, they are still insufficient for acoustic modeling, especially critical for languages with limited resources. Hence, this paper proposes a novel approach and outlines the methodological aspects required to create a \textit{corpus} with broad phonetic coverage for a low-resourced language, Brazilian Portuguese. Our methodology includes text dataset collection up to a sentence selection algorithm based on triphone distribution. Furthermore, we propose a new phonemic classification according to acoustic-articulatory speech features since the absolute number of distinct triphones, or low-probability triphones, does not guarantee an adequate representation of every possible combination. Using our algorithm, we achieve a 55.8\% higher percentage of distinct triphones -- for samples of similar size -- while the currently available phonetic-rich corpus, CETUC and TTS-Portuguese, 12.6\% and 12.3\% in comparison to a non-phonetically rich dataset.<|reference_end|>
@article{amadeus2024phonetically,
    title={Phonetically rich corpus construction for a low-resourced language},
    author={Marcellus Amadeus and William Alberto Cruz Casta~neda and Wilmer
  Lobato and Niasche Aquino},
    journal={arXiv preprint arXiv:2402.05794},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.05794},
    primaryClass={cs.CL cs.AI}
}