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!
Ne ƚa stragrande magioransa de i database par l’aprendimento vocaƚe catemo na neta sproporsione demografica a favore de ƚe voci <articleLink>maschiƚi e de clase media</articleLink>. Invese i asenti e i dialeti asocià a i grupi xà de par sé marginalixà, i riceve na rapresentasion minore ne i dataset par l’aprendimento de'l software. Inoltre diversi dispoxitivi i fadiga a conprendere ƚe voci feminiƚi. Eco parché voƚemo che el nostro database sia così vario.