Bias in Automated Speaker Recognition

Explore the critical issue of bias in automated speaker recognition systems in this insightful 17-minute conference talk presented by Wiebke Toussaint and Aaron Yi Ding at the Association for Computing Machinery (ACM). Delve into the challenges and implications of algorithmic bias in voice recognition technology, examining how these systems may inadvertently discriminate against certain groups based on factors such as accent, dialect, or speech patterns. Gain valuable insights into the potential consequences of biased speaker recognition in various applications, from security systems to voice-activated assistants. Learn about current research efforts and proposed solutions to mitigate bias and improve the fairness and accuracy of automated speaker recognition technologies.