Gender and Dialect Bias in YouTube's Automatic Captions

This project evaluates the accuracy of YouTube{'}s automatically-generated captions across two genders and five dialect groups. Speakers{'} dialect and gender was controlled for by using videos uploaded as part of the {``}accent tag challenge{''}, where speakers explicitly identify their language background. The results show robust differences in accuracy across both gender and dialect, with lower accuracy for 1) women and 2) speakers from Scotland. This finding builds on earlier research finding that speaker{'}s sociolinguistic identity may negatively impact their ability to use automatic speech recognition, and demonstrates the need for sociolinguistically-stratified validation of systems.