Voice assistants (VA) have become prevalent on a wide range of personal devices such as
smartphones and smart speakers. As companies build voice assistants with extra …

Abstract Machine learning methods are extensively used for processing and analysing
speech signals by virtue of their performance gains over multiple domains. Deep learning …

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 …

In authentication scenarios, applications of practical speaker verification systems usually
require a person to read a dynamic authentication text. Previous studies played an audio …

Conventionally, the extraction of hand-crafted acoustic features has been separated from the
task of establishing robust machine-learning models in speech processing. The manual …

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

Adversarial attack approaches to speaker identification either need high computational cost
or are not very effective, to our knowledge. To address this issue, in this letter, we propose a …

Deep neural networks (DNNs) are widely used for computer vision tasks. However, it has
been shown that deep models are vulnerable to adversarial attacks—that is, their …

While speaker identification (SI) systems based on deep neural network (DNN) have been
widely applied in securityrelated practical tasks, more and more attention has been attracted …

Generative Adversarial Networks (GANs) have the ability to generate images that are
visually indistinguishable from real images. However, recent studies have revealed that …