Humans can identify a speaker by listening to their voice, over the telephone, or on any
digital devices. Acquiring this congenital human competency, authentication technologies …

Deep learning has become a predominant method for solving data analysis problems in
virtually all fields of science and engineering. The increasing complexity and the large …

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 …

In neural network based speaker verification, speaker embedding is expected to be
discriminative between speakers while the intra-speaker distance should remain small. A …

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

In this study, we investigate self-supervised representation learning for speaker verification
(SV). First, we examine a simple contrastive learning approach (SimCLR) with a momentum …

This paper presents a novel Arabic Sign Language (ArSL) recognition system, using
selected 2D hands and body key points from successive video frames. The system …

Self-supervised learning (SSL) has drawn an increased attention in the field of speech
processing. Recent studies have demonstrated that contrastive learning is able to learn …

Speaker recognition is related to human biometrics dealing with the identification of
speakers from their speech. Speaker recognition is an active research area and being …

The concept of Acoustic Source Identification (ASI), which refers to the process of identifying
noise sources has attracted increasing attention in recent years. The ASI technology can be …