Speaker recognition is a task that identifies the speaker from multiple audios. Recently,
advances in deep learning have considerably boosted the development of speech signal …

Automatic speaker verification (ASV) plays a critical role in security-sensitive environments.
Regrettably, the reliability of ASV has been undermined by the emergence of spoofing …

Adversarial attacks pose a severe security threat to the state-of-the-art speaker identification
systems, thereby making it vital to propose countermeasures against them. Building on our …

Adversarial examples of speaker verification (SV) systems are the clean audio recordings
added with imperceptible perturbation. They are generated to manipulate the decision of SV …

It is known that deep neural networks are vulnerable to adversarial attacks. Although
Automatic Speaker Verification (ASV) built on top of deep neural networks exhibits robust …

Speaker verification (SV) systems have been widely used in smartphones and Internet of
Things devices to identify legitimate users. In recent work, it has been shown that adversarial …

Speaker verification systems use human voices as an important biometric to identify
legitimate users, thus adding a security layer to voice-controlled Internet-of-things smart …

Adversarial examples have proven to threaten speaker identification systems, and several
countermeasures against them have been proposed. In this paper, we propose a method to …

Abstract Automatic Speaker Verification (ASV) is extensively used in many security-sensitive
domains, but the increasing prevalence of adversarial attacks has seriously compromised …

Speech recognition technology has been applied to all aspects of our daily life, but it faces
many security issues. One of the major threats is the adversarial audio examples, which may …