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!
Ikédé jôga li bitoga bi mayaa ma makiñ di mbéna ndigi koba le ñgim i mintén mi mapôdôl mi ñgim i nya i bôt ñwon mi ntôl mu kiki bo <articleLink>bôlôm ni bôt ba bigwel moo</articleLink. Bisoolene bi makiñ bi nhôlhana ni unu ntén njel bi mbéna ndigi la solol ni nigle makiñ ma inyaa bôt ba mbôñôl nya yap i makiñ. Inya i makiñ i nt́ôl bé nene i mayaa ma makiñ ba ñgwélél inyu ihôlôs lisolol makiñ, iyé ma diyende di bôt tole diyende di maloñ. Ndun i yé le makeñge inyu liniiga bikey lisolol ni linigle makiñ ma bôñlak yak makiñ ma bôda. Inyu hala nyen ndôlôk i makiñ i yé nseñ ngandak munu iyés toga i mayaa.