Abstract:Automated speaker recognition uses data processing to identify speakers by their voice. Today, automated speaker recognition technologies are deployed on billions of smart devices and in services such as call centres. Despite their wide-scale deployment and known sources of bias in face recognition and natural language processing, bias in automated speaker recognition has not been studied systematically. We present an in-depth empirical and analytical study of bias in the machine learning development workflow … Show more
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