most citedVocoder drift in x-vector-based speaker anonymization

2 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

2D-Malafide: Adversarial Attacks Against Face Deepfake Detection Systems

Chiara Galdi, Michele Panariello, Massimiliano Todisco +1

We introduce 2D-Malafide, a novel and lightweight adversarial attack designed to deceive face deepfake detection systems. Building upon the concept of 1D convolutional perturbation…

eess.AS2024

Malacopula: adversarial automatic speaker verification attacks using a neural-based generalised Hammerstein model

Massimiliano Todisco, Michele Panariello, Xin Wang +3

We present Malacopula, a neural-based generalised Hammerstein model designed to introduce adversarial perturbations to spoofed speech utterances so that they better deceive automat…

eess.AS2024

Preserving spoken content in voice anonymisation with character-level vocoder conditioning

Michele Panariello, Massimiliano Todisco, Nicholas Evans

Voice anonymisation can be used to help protect speaker privacy when speech data is shared with untrusted others. In most practical applications, while the voice identity should be…

eess.AS2024

The VoicePrivacy 2022 Challenge: Progress and Perspectives in Voice Anonymisation

Michele Panariello, Natalia Tomashenko, Xin Wang +7

The VoicePrivacy Challenge promotes the development of voice anonymisation solutions for speech technology. In this paper we present a systematic overview and analysis of the secon…

eess.AS2023

Fairness and Privacy in Voice Biometrics:A Study of Gender Influences Using wav2vec 2.0

Oubaida Chouchane, Michele Panariello, Chiara Galdi +2

This study investigates the impact of gender information on utility, privacy, and fairness in voice biometric systems, guided by the General Data Protection Regulation (GDPR) manda…

eess.AS20231 cited

Vocoder drift compensation by x-vector alignment in speaker anonymisation

Michele Panariello, Massimiliano Todisco, Nicholas Evans

For the most popular x-vector-based approaches to speaker anonymisation, the bulk of the anonymisation can stem from vocoding rather than from the core anonymisation function which…