The human voice production system is an intricate biological device capable of modulating
pitch and loudness. Inherent internal and/or external factors often damage the vocal folds …

In the last decade, the implementation of machine learning algorithms in the analysis of
voice disorder is paramount in order to provide a non-invasive voice pathology detection by …

Objectives Auditory-perceptual voice analysis is a standard method for quantifying
pathological voice quality, but perceptual ratings are based on subjective evaluations and …

To improve the performance of pathological voice detection and classification, gammatone
spectral latitude (GTSL) features were proposed. GTSL features are inspired by the …

This paper presents a convolutional neural network (CNN) based automated noninvasive
voice pathology detection system. The proposed system functions in two steps. First, it …

Introduction Over the past decade, several machine learning (ML) algorithms have been
investigated to assess their efficacy in detecting voice disorders. Literature indicates that ML …

Purpose The purpose of this study was to determine concurrent validity of the Grade,
Roughness, Breathiness, Asthenia, and Strain (GRBAS) and Consensus Auditory …

This work describes a novel methodology to characterize voice diseases by using nonlinear
dynamics, considering different complexity measures that are mainly based on the analysis …

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

Auditory perceptual evaluation is considered the gold standard for assessing voice quality,
but its reliability is limited due to inter-rater variability and coarse rating scales. This study …