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!
Datasets nnzhi dza u amba dzi re hone dzi gudiswa hu na vhaimeleli vha nnzhi vha vhubvo ho khetheaho zwa ita uri dzi imeleleswe <articleLink>vhanna na vhathu vhuimo ha vhukati</articleLink>. Kuambele na dzi dialect dzi sa imelelwi zwavhuḓi musi hu tshi itwa dzi data set dza u gudisa dzi tshimbidzana na zwigwada zwa vhathu vhane vha si dzhielwe nṱha. Mitshini minzhi i a konḓelwa na u pfesesa maipfi a vhafumakadzi. Ndi ngazwo kha database yashu ri tshi khou ṱoḓa maipfi o fhambananaho!