Raw waveform acoustic modelling has recently received increasing attention. Compared
with the task-blind hand-crafted features which may discard useful information …

Human ailments create an impact in altering the significant metabolism activities of the body
irrespective of various parts. Dysarthric speech is commonly known as Parkinson's disease …

Although the UA-Speech and TORGO databases of control and dysarthric speech are
invaluable resources made available to the research community with the objective of …

Objectives Auditory-perceptual evaluation frameworks, such as the grade-roughness-
breathiness-asthenia-strain (GRBAS) scale, are the gold standard for the quantitative …

Since the mental states of the speaker modulate speech, stress introduced by cognitive or
physical loads could be detected in the voice. The existing voice stress detection benchmark …

Speech representations which are robust to pathology-unrelated cues such as speaker
identity information have been shown to be advantageous for automatic dysarthric speech …

Speech emotion recognition plays a crucial role in analyzing psychological disorders,
behavioral decision‐making, and human‐machine interaction applications. However, the …

In this paper, we explore the effectiveness of deploying the raw phase and magnitude
spectra for dysarthric speech recognition, detection and classification. In particular, we …

Deep learning-based pathological speech detection approaches are gaining popularity as a
diagnostic tool to support time-consuming and subjective clinical assessments. While these …

Automatic pathological speech detection relies on deep learning (DL), showing promising
performance for various pathologies. Despite the critical importance of robustness in …