The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …

At the time of writing this article, the world population is suffering from more than 2 million
registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona …

In this paper, we propose a method for automatically detecting various types of snore
sounds using image classification convolutional neural network (CNN) descriptors extracted …

Language is a universal human ability, acquired readily by young children, who otherwise
struggle with many basics of survival. And yet, language ability is variable across …

Due to the complex and intricate nature associated with their production, the acoustic-
prosodic properties of a speech signal are modulated with a range of health related effects …

A range of demographic variables influences how much speech young children hear.
However, because studies have used vastly different sampling methods, quantitative …

Automatic affect recognition in real-world environments is an important task towards a
natural interaction between humans and machines. The recent years, several …

Computational paralinguistic analysis is increasingly being used in a wide range of cyber
applications, including security-sensitive applications such as speaker verification …

Speech emotion recognition (SER) plays an important role in intelligent speech interaction.
One vital challenge in SER is to extract emotion-relevant features from speech signals. In …

Alzheimer's dementia is a progressive neurodegenerative disease that causes cognitive and
physical impairment. It severely deteriorates the quality of life in affected individuals. An …