Advances in privacy preservation and fairness assessment for voice biometrics

This thesis explores the importance of strengthening compliance with regulatory frameworks like the European General Data Protection Regulation (GDPR) in relation to data privacy and fairness in the field of voice biometrics focusing specifically on Automatic Speaker Verification (ASV). Through the use of cryptographic techniques, data perturbation methods and disentangled representation learning techniques our research aims to protect individuals privacy by effectively safeguarding sensitive attributes. Additionally our study assesses the fairness of ASV systems to identify potential disparities in outcomes. This assessment lays a foundation for developing systems that not only prioritize fairness but also adhere to regulatory requirements promoting a balanced approach to privacy and fairness, in voice biometrics technology.