Hypokinetic dysarthria (HD) occurs in 90% of Parkinson's disease (PD) patients. It manifests
specifically in the areas of articulation, phonation, prosody, speech fluency, and faciokinesis …

Background Digital biomarkers are increasingly used in clinical decision support for various
health conditions. Speech features as digital biomarkers can offer insights into underlying …

This paper presents the possibilities of using speech signal processing, analysis and
regression methods in the context of assessment of neurological state in Parkinson's …

Two decades ago it would have been hard to foresee the remarkable growth in the use of
artificial intelligence (AI) in the physical and life sciences. But there is a simple explanation …

In this paper, MFCC and PLP voice features extracted using Single Taper Smooth (STS)
window and Thomson Multitaper (TMT) windowing technique together with a neural network …

The aim of this study presented in this paper is to determine the choice of the appropriate
wavelet analyzer with the method of extraction of MFCC coefficients for an assistance in the …

Detecting Parkinson's disease (PD) based on voice analysis is meaningful due to its non-
invasion and convenience. Traditional features adopted for PD detection are often hand …

The objectives of the dysarthria assessment are to discriminate dysarthric speech from
normal speech, to estimate the severity of dysarthria in terms of the dysarthric speech …

To diagnose Parkinson's disease (PD), it is necessary to monitor the progression of
symptoms. Unfortunately, diagnosis is often confirmed years after the onset of the disease …

Parkinson Disease (PD) is a severe chronic and progressive neuro-degenerative nerve
disease effects the central nervous system associated with the dopamine deficiency …