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arXiv · 2505.08978

Inference Attacks for X-Vector Speaker Anonymization

Luke Bauer·Wenxuan Bao·Malvika Jadhav·Vincent Bindschaedler
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Abstract

We revisit the privacy-utility tradeoff of x-vector speaker anonymization. Existing approaches quantify privacy through training complex speaker verification or identification models that are later used as attacks. Instead, we propose a novel inference attack for de-anonymization. Our attack is simple and ML-free yet we show experimentally that it outperforms existing approaches.

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Luke Bauer, Wenxuan Bao, Malvika Jadhav, Vincent Bindschaedler. 2025-05-13. Inference Attacks for X-Vector Speaker Anonymization. https://arxiv.org/abs/2505.08978

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