Author

Ming Li

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Preprint Oct 2026

Voice Anonymization Made Simple: Training-Free Anonymization with Projected Classifier-Free Guidance

Voice anonymization aims to conceal speaker identity while preserving linguistic and paralinguistic information, yet many existing methods require dedicated training. We propose a training-free, two-stage anonymization method for pretrained flow-matching voice conversion systems. In the condition-construction stage, th...

Xiang Shi, Han Zhu, Ming Li et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Exploiting Acoustic and Content-Oriented Speaker Verification Attacks Against Multilingual Voice Anonymization

Attacker ASV systems for voice anonymization have been studied primarily in English, leaving their behavior in multilingual settings largely unexplored. Conventional ASV has shown that both acoustic and contextual information are important for multilingual speaker verification. Inspired by this, we investigate whether...

Ridwan Arefeen, Ze Li, Rong Tong et al. · 0 citations