This paper presents a novel approach for automated dysarthria detection and severity
assessment using a variable short-time Fourier transform layered convolutional neural …

Dysarthria is a medical condition that impairs an individual's ability to speak clearly due to
muscle weakness or paralysis. To diagnose and monitor dysarthria severity, this article …

We propose a Perceiver-based sequence classifier to detect abnormalities in speech
reflective of several neurological disorders. We combine this classifier with a Universal …

Speech is known to carry health-related attributes, which has emerged as a novel venue for
remote and long-term health monitoring. However, existing models are usually tailored for a …

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 …

Speech production is a complex phenomenon, wherein the brain orchestrates a sequence
of processes involving thought processing, motor planning, and the execution of articulatory …

Despite the promising performance of state of the art approaches for Parkinsons Disease
(PD) detection, these approaches often analyze individual speech segments in isolation …

Automatic pathological speech detection approaches yield promising results in identifying
various pathologies. These approaches are typically designed and evaluated for …

Recently proposed automatic pathological speech detection approaches rely on
spectrogram input representations or wav2vec2 embeddings. These representations may …