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!
Kuma kunnafonidilan fanba bɛ dege ni jamanaden hakɛ dɔw jirali ye kojugu min bɛ na ni ɲɛmajɔbaliya ye <articleLink>cɛ ni cɛmancɛlamɔgɔw</articleLink> la. Fɔcogo ni kanfɔcogo minnu ka teli ka kɛ ka caya kalan kunnafonidilanw kɔnɔ, a ka c’a la, olu bɛ tali kɛ mɔgɔw kuluw la minnu bɛ danfara la kaban. Masina caman fana bɛ gɛlɛya sɔrɔ ka musow kanw faamuya.