AIMC Topic: Voice Disorders

Clear Filters Showing 21 to 30 of 32 articles

A Survey on Machine Learning Approaches for Automatic Detection of Voice Disorders.

Journal of voice : official journal of the Voice Foundation Oct 11, 2018
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 and result in some change of voice. The consequences are reflected in...
Voice Disorders Larynx Voice Quality Predictive Value of Tests Acoustics Pattern Recognition, Automated Wavelet Analysis Humans Machine Learning Reproducibility of Results Diagnosis, Computer-Assisted
View on PubMed DOI

Demographic and Symptomatic Features of Voice Disorders and Their Potential Application in Classification Using Machine Learning Algorithms.

Folia phoniatrica et logopaedica : official organ of the International Association of Logopedics and Phoniatrics (IALP) Sep 5, 2018
BACKGROUND: Studies have used questionnaires of dysphonic symptoms to screen voice disorders. This study investigated whether the differential presentation of demographic and symptomatic features can be applied to computerized classification.
Humans Neural Networks, Computer Algorithms Retrospective Studies Female Aged Adult Male Demography Glottis Middle Aged Sex Factors Vocal Cord Paralysis Smoking Severity of Illness Index Voice Disorders Age Factors Alcohol Drinking Laryngeal Neoplasms Supervised Machine Learning Symptom Assessment Voice Quality Wounds and Injuries
View on PubMed DOI

Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.

Journal of voice : official journal of the Voice Foundation Oct 12, 2016
OBJECTIVES: Speech signal processing techniques have provided several contributions to pathologic voice identification, in which healthy and unhealthy voice samples are evaluated. A less common approach is to identify laryngeal pathologies, for which...
Voice Quality Speech Acoustics Vocal Cord Paralysis Vocal Cords Female Voice Disorders Humans Speech Production Measurement Male Databases, Factual Predictive Value of Tests Case-Control Studies Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Pattern Recognition, Automated Support Vector Machine Edema
View on PubMed DOI

A generalized procedure for analyzing sustained and dynamic vocal fold vibrations from laryngeal high-speed videos using phonovibrograms.

Artificial intelligence in medicine Oct 30, 2015
OBJECTIVE: This work presents a computer-based approach to analyze the two-dimensional vocal fold dynamics of endoscopic high-speed videos, and constitutes an extension and generalization of a previously proposed wavelet-based procedure. While most a...
Wavelet Analysis Vocal Cords Voice Disorders Laryngoscopy Aged Vibration Phonation Principal Component Analysis Adult Humans Video Recording Middle Aged Larynx Biomechanical Phenomena Female Voice Quality Case-Control Studies Image Interpretation, Computer-Assisted Reproducibility of Results Pattern Recognition, Automated Time Factors Support Vector Machine Predictive Value of Tests Male
View on PubMed DOI

Differentiability of voice disorders through explainable AI.

Scientific reports May 25, 2025
The voice can be affected by various types of pathology. The phoniatric medical examination is the acoustic analysis, which evaluates the characteristic parameters extracted from the vocal signal. Computer-assisted decision-making systems can help sp...
Dysphonia Humans Artificial Intelligence Voice Voice Disorders
View on PubMed DOI

A hybrid approach for binary and multi-class classification of voice disorders using a pre-trained model and ensemble classifiers.

BMC medical informatics and decision making May 1, 2025
Recent advances in artificial intelligence-based audio and speech processing have increasingly focused on the binary and multi-class classification of voice disorders. Despite progress, achieving high accuracy in multi-class classification remains ch...
Support Vector Machine Humans Female Voice Disorders Male Deep Learning
View on PubMed DOI

Automatic GRBAS Scoring of Pathological Voices using Deep Learning and a Small Set of Labeled Voice Data.

Journal of voice : official journal of the Voice Foundation May 1, 2025
OBJECTIVES: Auditory-perceptual evaluation frameworks, such as the grade-roughness-breathiness-asthenia-strain (GRBAS) scale, are the gold standard for the quantitative evaluation of pathological voice quality. However, the evaluation is subjective; ...
Speech Acoustics Voice Disorders Speech Production Measurement Voice Quality Acoustics Observer Variation Automation Judgment Female Reproducibility of Results Adult Male Severity of Illness Index Deep Learning Time Factors Predictive Value of Tests Signal Processing, Computer-Assisted Humans Neural Networks, Computer
View on PubMed DOI

Detection of Neurogenic Voice Disorders Using the Fisher Vector Representation of Cepstral Features.

Journal of voice : official journal of the Voice Foundation May 1, 2025
Neurogenic voice disorders (NVDs) are caused by damage or malfunction of the central or peripheral nervous system that controls vocal fold movement. In this paper, we investigate the potential of the Fisher vector (FV) encoding in automatic detection...
Humans Adult Male Middle Aged Case-Control Studies Support Vector Machine Databases, Factual Female Reproducibility of Results Aged Young Adult Phonation Voice Quality Dysphonia Speech Acoustics Vocal Cord Paralysis Predictive Value of Tests Vocal Cords Signal Processing, Computer-Assisted Voice Disorders Acoustics Speech Production Measurement Sound Spectrography
View on PubMed DOI

Developing a smart system for binary classification of disordered voices using machine learning.

American journal of otolaryngology Jan 1, 2025
OBJECTIVES: Voice disorder is characterized by disruptions in voice quality caused by issues in vocal fold vibration during phonation. The study explored the application of machine learning, based on the Random Forest (RF) and Decision Tree (DT) mode...
Humans Machine Learning Databases, Factual Female ROC Curve Aged Decision Trees Young Adult Speech Acoustics Adult Voice Disorders Male Voice Quality Middle Aged
View on PubMed DOI

Pathological voice classification based on multi-domain features and deep hierarchical extreme learning machine.

The Journal of the Acoustical Society of America Jan 1, 2023
The intelligent data-driven screening of pathological voice signals is a non-invasive and real-time tool for computer-aided diagnosis that has attracted increasing attention from researchers and clinicians. In this paper, the authors propose multi-do...
Humans Algorithms Deep Learning Entropy Voice Voice Disorders
View on PubMed DOI
Popular Topics
Recent Journals