Language Independent Speaker Anonymization

Language-independent speaker anonymization aims to transform speech recordings to mask speaker identity while preserving the linguistic content, crucial for privacy protection in multilingual contexts. Recent research focuses on developing robust systems using self-supervised learning and multilingual adaptations of existing models, often addressing challenges posed by domain mismatch between training and testing data (e.g., different languages or recording conditions). These efforts are significant for advancing privacy-preserving technologies and improving the accessibility of speech processing tools across diverse languages.