2 citations · 5 across the 21 of their papers we have counts for
6 papers · 1 filter
Speaker anonymization using neural audio codec language models
Michele Panariello, Francesco Nespoli, Massimiliano Todisco +1
The vast majority of approaches to speaker anonymization involve the extraction of fundamental frequency estimates, linguistic features and a speaker embedding which is perturbed t…
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…
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…
Differentially Private Adversarial Auto-Encoder to Protect Gender in Voice Biometrics
Oubaïda Chouchane, Michele Panariello, Oualid Zari +4
Over the last decade, the use of Automatic Speaker Verification (ASV) systems has become increasingly widespread in response to the growing need for secure and efficient identity v…
Malafide: a novel adversarial convolutive noise attack against deepfake and spoofing detection systems
Michele Panariello, Wanying Ge, Hemlata Tak +2
We present Malafide, a universal adversarial attack against automatic speaker verification (ASV) spoofing countermeasures (CMs). By introducing convolutional noise using an optimis…
Vocoder drift in x-vector-based speaker anonymization
Michele Panariello, Massimiliano Todisco, Nicholas Evans
State-of-the-art approaches to speaker anonymization typically employ some form of perturbation function to conceal speaker information contained within an x-vector embedding, then…