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eess.AS2026

In Defense of Using Worst-case Privacy Disclosure as Privacy Evaluation Metric of Voice Anonymization

Xin Wang, Xiaoxiao Miao

The voice anonymization community mainly uses Equal Error Rate (EER) to evaluate the performance of voice identity protection. While alternative metrics such as privacy-ZEBRA and a…

eess.AS2025

Target speaker anonymization in multi-speaker recordings

Natalia Tomashenko, Junichi Yamagishi, Xin Wang +2

Most of the existing speaker anonymization research has focused on single-speaker audio, leading to the development of techniques and evaluation metrics optimized for such conditio…

eess.AS2025

Speaker Privacy and Security in the Big Data Era: Protection and Defense against Deepfake

Liping Chen, Kong Aik Lee, Zhen-Hua Ling +4

In the era of big data, remarkable advancements have been achieved in personalized speech generation techniques that utilize speaker attributes, including voice and speaking style,…

eess.AS2025

Mitigating Language Mismatch in SSL-Based Speaker Anonymization

Zhe Zhang, Wen-Chin Huang, Xin Wang +2

Speaker anonymization aims to protect speaker identity while preserving content information and the intelligibility of speech. However, most speaker anonymization systems (SASs) ar…

eess.AS2024

Spoofing-Aware Speaker Verification Robust Against Domain and Channel Mismatches

Chang Zeng, Xiaoxiao Miao, Xin Wang +2

In real-world applications, it is challenging to build a speaker verification system that is simultaneously robust against common threats, including spoofing attacks, channel misma…