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!
大多數的語音數據庫的語音來源偏重於某群特定人口，造成結果偏向於<articleLink>男性與中產階級</articleLink>。而在這些訓練機械的數據之中，各種不同的口音與方言與被邊緣化的人群常有所關連。許多機器也很難理解女性的聲音。 這就是為什麼我們的語音數據庫應該海納百川，收集各種聲音！