175 citations · 810 across the 46 of their papers we have counts for
10 papers · 1 filter
SynVox2: Towards a privacy-friendly VoxCeleb2 dataset
Xiaoxiao Miao, Xin Wang, Erica Cooper +5
The success of deep learning in speaker recognition relies heavily on the use of large datasets. However, the data-hungry nature of deep learning methods has already being question…
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…
Spoofing attack augmentation: can differently-trained attack models improve generalisation?
Wanying Ge, Xin Wang, Junichi Yamagishi +2
A reliable deepfake detector or spoofing countermeasure (CM) should be robust in the face of unpredictable spoofing attacks. To encourage the learning of more generaliseable artefa…
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…
Towards single integrated spoofing-aware speaker verification embeddings
Sung Hwan Mun, Hye-jin Shim, Hemlata Tak +12
This study aims to develop a single integrated spoofing-aware speaker verification (SASV) embeddings that satisfy two aspects. First, rejecting non-target speakers' input as well a…
Can spoofing countermeasure and speaker verification systems be jointly optimised?
Wanying Ge, Hemlata Tak, Massimiliano Todisco +1
Spoofing countermeasure (CM) and automatic speaker verification (ASV) sub-systems can be used in tandem with a backend classifier as a solution to the spoofing aware speaker verifi…