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 …

Abstract Machine learning has immense potential to enhance diagnostic and intervention
research in the behavioral sciences, and may be especially useful in investigations involving …

Speech emotion recognition is a vital and challenging task that the feature extraction plays a
significant role in the SER performance. With the development of deep learning, we put our …

Work on voice sciences over recent decades has led to a proliferation of acoustic
parameters that are used quite selectively and are not always extracted in a similar fashion …

Depression is a common, but serious mental disorder that affects people all over the world.
Besides providing an easier way of diagnosing the disorder, a computer-aided automatic …

The objective of this paper is to present the state of-the-art relating to automatic speech and
voice analysis techniques as applied to the monitoring of patients suffering from Alzheimer's …

Paralinguistic analysis is increasingly turning into a mainstream topic in speech and
language processing. This article aims to provide a broad overview of the constantly …

This book reports on an outstanding thesis that has significantly advanced the state-of-the-
art in the automated analysis and classification of speech and music. It defines several …

Automatically recognizing human emotions from spontaneous and non-prototypical real-life
data is currently one of the most challenging tasks in the field of affective computing. This …

Despite the widespread use of supervised learning methods for speech emotion recognition,
they are severely restricted due to the lack of sufficient amount of labelled speech data for …