Over the past decades, a particular focus is given to research on machine learning
techniques for speech processing applications. However, in the past few years, research …

Automatic speaker verification (ASV) systems are enhanced enough, that industry is
attracted to use them practically in security systems. However, vulnerability of these systems …

A great deal of recent research effort on speech spoofing countermeasures has been
invested into back-end neural networks and training criteria. We contribute to this effort with …

Voice biometric authentication is increasingly gaining adoption in organisations with high-
volume identity verifications and for providing access to physical and other virtual spaces. In …

Audio spoofing attacks not only increasingly pose a threat to automatic speaker verification
systems but also have the potential to destabilize national security (eg, by creating fake …

In recent years, automatic speaker verification (ASV) is used extensively for voice biometrics.
This leads to an increased interest to secure these voice biometric systems for real-world …

Audio deepfakes have been increasingly emerging as a potential source of deceit, with the
development of avant-garde methods of synthetic speech generation. Hence, differentiating …

With the advancements in deep learning and other techniques, synthetic speech is getting
closer to a natural sounding voice. Some of the state-of-art technologies achieve such a high …

In this letter, we introduce CGDNet, a cost-efficient hybrid neural network composed of a
shallow convolutional network, a gated recurrent unit, and a deep neural network, for robust …

The ability to distinguish between authentic and fake audio is become increasingly difficult
due to the increasing accuracy of text-to-speech models, posing a serious threat to speaker …