Voice Privacy

Voice privacy research focuses on developing methods to anonymize speech while preserving its intelligibility and emotional content, thereby protecting speaker identity from malicious use. Current efforts concentrate on improving speaker anonymization techniques, often employing disentanglement models (like VAEs), adversarial learning, and modifications to fundamental frequency (F0) trajectories within voice conversion systems. This field is crucial for mitigating privacy risks associated with increasingly sophisticated speech technologies and has significant implications for both the development of responsible AI and the protection of individual privacy in various applications.