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!
Ko'pgina nutq ma'lumotlar bazalari ma'lum demografik ma'lumotlarning haddan tashqari taqdim etilishi bilan o'qitiladi, natijada <articleLink> erkak va o'rta sinf </articleLink> tomon yo'naltiriladi. Ta'lim ma'lumotlari to'plamida etarlicha aks ettirilmaydigan urg'u va lahjalar, odatda allaqachon chetga chiqqan odamlar guruhlari bilan bog'liq. Ko'pgina mashinalar ayollarning ovozini tushunish uchun ham kurashmoqda. Shuning uchun bizning ovozli ma'lumotlar bazamizda xilma-xillikni xohlaymiz!