Voice biometrics are being implemented globally in large scale applications such as remote banking, government e-services, transportation and building security access, autonomous vehicles, and healthcare. They have been integrated in numerous apps, often coupled with face biometrics and artificial intelligence methods. Voice biometrics products and solutions must meet three key requirements for the success in their deployment: they must be highly trustable regarding privacy protection; easy to use and always be available.

• Chapter 1: Introduction
• Chapter 2: Fundamentals of voice biometrics: classical and machine learning approaches learning approaches
• Chapter 3: Voice biometrics: attacker's perspective
• Chapter 4: Voice biometrics: privacy in paralinguistic and extralinguistic tasks for health applications
• Chapter 5: Voice privacy in biometrics: speaker de-identification
• Chapter 6: Performance evaluation of voice biometrics solutions
• Chapter 7: Voice biometrics: how the technology is standardized
• Chapter 8: Voice biometrics: perspective from the industry
• Chapter 9: Joining forces of voice and facial biometrics: a case study in the scope of NIST SRE'19
• Chapter 10: Voice biometrics: future trends and challenges ahead