Most speech databases are trained with an overrepresentation of certain demographics which results in a bias towards <articleLink>male and middle class</articleLink>. Accents and dialects that tend to be under-represented in training data sets are typically associated with groups of people who are already marginalised. Many machines also struggle to understand female voices. This is why in our voice database we want variety!
Tidathabeyisi to tala ta mbulavulo ti leteriwile hi ku yimela ku tlula mpimo ka nhlayo yo karhi ya vaaki leswi endlaka leswaku ku va na ku va na xihlawuhlawu eka <articleLink>xiyimo xa xinuna na xa le xikarhi</articleLink>. Ti-accent na tindzimi leti talaka ku va ti nga yimeriwi ngopfu eka tisethi ta datha ya ndzetelo hi ntolovelo ti fambelanisiwa na mintlawa ya vanhu lava se va nga le tlhelo.  Michini yo tala na yona yi lwela ku twisisa marito ya vavasati. Leswi hi swona swi endlaka leswaku eka database ya hina ya rito hi lava ku hambana-hambana!