Tootfinder

A Study of the Removability of Speaker-Adversarial Perturbations
Liping Chen, Chenyang Guo, Kong Aik Lee, Zhen-Hua Ling, Wu Guo
https://arxiv.org/abs/2510.09504 https://

A Study of the Removability of Speaker-Adversarial Perturbations
Recent advancements in adversarial attacks have demonstrated their effectiveness in misleading speaker recognition models, making wrong predictions about speaker identities. On the other hand, defense techniques against speaker-adversarial attacks focus on reducing the effects of speaker-adversarial perturbations on speaker attribute extraction. These techniques do not seek to fully remove the perturbations and restore the original speech. To this end, this paper studies the removability of spe…

Investigation of perception inconsistency in speaker embedding for asynchronous voice anonymization
Rui Wang, Liping Chen, Kong Aik Lee, Zhengpeng Zha, Zhenhua Ling
https://arxiv.org/abs/2510.05718

Investigation of perception inconsistency in speaker embedding for asynchronous voice anonymization
Given the speech generation framework that represents the speaker attribute with an embedding vector, asynchronous voice anonymization can be achieved by modifying the speaker embedding derived from the original speech. However, the inconsistency between machine and human perceptions of the speaker attribute within the speaker embedding remains unexplored, limiting its performance in asynchronous voice anonymization. To this end, this study investigates this inconsistency via modifications to s…