The time delay neural network (TDNN) represents one of the state-of-the-art of neural
solutions to text-independent speaker verification. However, they require a large number of …

Speaker Verification (SV) is widely deployed in mobile systems to authenticate legitimate
users by using their voice traits. In this work, we propose a backdoor attack MasterKey, to …

Abstract Time Delay Neural Network (TDNN)-based speaker embeddings extraction have
become the dominant approach for text-independent speaker verification. Several single …

Extraction of a speaker embedding vector plays an important role in deep learning-based
speaker verification. In this contribution, to extract speaker discriminant utterance level …

Automatic speaker verification (ASV) faces an unprecedented problem due to mask-wearing
speakers, a consequence of COVID-19. Masked speakers unconsciously alter their normal …

Cross-domain speaker recognition (SR) can be improved by unsupervised domain
adaptation (UDA) algorithms. UDA algorithms often reduce domain mismatch at the cost of …

Optimal transport (OT) can be applied to cross-domain adaptation in speaker verification
(SV) by converting speakers' probability distributions from source to target domains …

Convolutional neural networks (CNNs), such as the time-delay neural network (TDNN), have
shown their remarkable capability in learning speaker embedding. However, they …

In this paper, we propose a new hybrid system for extracting a speaker embedding vector.
More specifically, the proposed system employs a multi-level global-local statistics pooling …

Various mismatchedconditions result in performance degradation of the speaker verification
(SV) systems. To address this issue, we extract robust speaker representations by devising a …