Over the past few years, significant progress has been made in the field of presentation
attack detection (PAD) for automatic speaker recognition (ASV). This includes the …

Human voices can be used to authenticate the identity of the speaker, but the automatic
speaker verification (ASV) systems are vulnerable to voice spoofing attacks, such as …

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 …

The constant Q transform (CQT) has been shown to be one of the most effective speech
signal pre-transforms to facilitate synthetic speech detection, followed by either hand-crafted …

Text-independent speaker verification against short utterances is still challenging despite of
recent advances in the field of speaker recognition with i-vector framework. In general, to get …

The effectiveness of introducing deep neural networks into conventional speaker recognition
pipelines has been broadly shown to benefit system performance. A novel text-independent …

By employing generative deep learning techniques, Deepfakes are created with the intent to
create mistrust in society, manipulate public opinion and political decisions, and for other …

Significant advancements made in the generation of deepfakes have caused security and
privacy issues. Attackers can easily impersonate a person's identity in an image by replacing …

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 …

Several methods for synthetic audio speech generation have been developed in the
literature through the years. With the great technological advances brought by deep …