Research on speaker recognition is extending to address the vulnerability in the wild
conditions, among which genre mismatch is perhaps the most challenging, for instance …

Speaker recognition systems (SRSs) have recently been shown to be vulnerable to
adversarial attacks, raising significant security concerns. In this work, we systematically …

Automatic assessment of depression from speech signals is affected by variabilities in
acoustic content and speakers. In this study, we focused on addressing these variabilities …

Physiological studies have illustrated that speech can be used as a biomarker to analyze the
severity of depression and different frequency bands of the speech spectrum contribute …

Adversarial attacks have been expanded to speaker recognition (SR). However, existing
attacks are often assessed using different SR models, recognition tasks and datasets, and …

This paper describes a novel end‐to‐end deep generative model‐based speaker
recognition system using prosodic features. The usefulness of variational autoencoders …

In this paper a novel cross-device text-independent speaker verification architecture is
proposed. Majority of the state-of-the-art deep architectures that are used for speaker …

Speaker recognition systems achieve good performance under controlled conditions.
However, in real-world conditions, the performance degrades drastically. The principal …

Little is known about human and machine speaker discrimination ability when utterances
are very short and the speaking style is variable. This study compares text-independent …

Physiological reports have confirmed that there are differences in speech signals between
depressed and healthy individuals. Therefore, as an application in the field of affective …