1 citations · 2 across the 15 of their papers we have counts for
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Why Do You Say It Like That? A Phoneme-Level Framework for Explainable Speech Deepfake Detection
Anna Taylor, Michele Panariello, Massimiliano Todisco +3
As the accuracy of speech deepfake detection improves with the use of self-supervised representations such as wav2vec 2.0 and HuBERT, understanding why the speech is classified as…
Positive-Incentive Noise Predictor for Adversarial Purification in Speaker Verification
Yibo Bai, Sizhou Chen, Michele Panariello +5
Modern automatic speaker verification (ASV) systems are vulnerable to adversarial perturbations. Diffusion-based purification has recently shown strong effectiveness against such p…
Latent Secret Spin: Keyed Orthogonal Rotations for Blind Speech Watermarking in Anisotropic Latent Spaces
Emma Coletta, Massimiliano Todisco, Michele Panariello +2
We introduce Latent Secret Spin (LSS), a blind speech watermarking method based on geometric operations in codec latent space. Based upon orthogonal rotations to principal componen…
Evaluating voice anonymisation using similarity rank disclosure
Shilpa Chandra, Matteo Pettenò, Nicholas Evans +7
The evaluation of voice anonymisation remains challenging. Current practice relies on automatic speaker verification metrics such as the equal error rate (EER). Performance estimat…
MDD: a Mask Diffusion Detector to Protect Speaker Verification Systems from Adversarial Perturbations
Yibo Bai, Sizhou Chen, Michele Panariello +3
Speaker verification systems are increasingly deployed in security-sensitive applications but remain highly vulnerable to adversarial perturbations. In this work, we propose the Ma…
Reference-free Adversarial Sex Obfuscation in Speech
Yangyang Qu, Michele Panariello, Massimiliano Todisco +1
Sex conversion in speech involves privacy risks from data collection and often leaves residual sex-specific cues in outputs, even when target speaker references are unavailable. We…