Parkinson's Disease (PD) affects speech in the form of dysphonia and hypokinetic
dysarthria. Multiple studies have evaluated PD's influence on different aspects of speech …

Parkinson's disease (PD) is a chronic neurodegenerative disease of that predominantly
affects the elderly in today's world. For the diagnosis of the early stages of PD, effective and …

More than 90% of patients with Parkinson's disease suffer from hypokinetic dysarthria. This
paper proposes a novel end-to-end deep learning model for Parkinson's disease detection …

Developing automatic methods to detect Parkinson's disease (PD) from speech has
attracted increasing interest as these techniques can potentially be used in telemonitoring …

Recently, we have witnessed Deep Learning methodologies gaining significant attention for
severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its …

Parkinson's Disease (PD) is among the most frequent neurological disorders. Approaches
that employ artificial intelligence and notably deep learning, have been extensively …

To distinguish pathological voices from healthy voices, automatic voice pathology detection
systems can be built using machine learning (ML) and deep learning (DL) techniques. To …

Recently, spectro-temporal representation of speech has been used in many fields of
speech processing. Owing to this, we explore the use of spectro-temporal representation for …

This paper proposed a novel approach for the detection and reconstruction of dysarthric
speech. The encoder-decoder model factorizes speech into a low-dimensional latent space …

Speech production can be regarded as a process where a time-varying vocal tract system
(filter) is excited by a time-varying excitation. In addition to its linguistic message, the speech …