AIMC Topic: Voice Quality

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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.
Vocal Cord Paralysis Voice Disorders Laryngeal Neoplasms Voice Quality Glottis Aged Adult Male Middle Aged Severity of Illness Index Age Factors Supervised Machine Learning Humans Sex Factors Neural Networks, Computer Smoking Algorithms Alcohol Drinking Retrospective Studies Symptom Assessment Female Wounds and Injuries Demography
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Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach.

Journal of voice : official journal of the Voice Foundation Mar 19, 2018
OBJECTIVES: Computerized detection of voice disorders has attracted considerable academic and clinical interest in the hope of providing an effective screening method for voice diseases before endoscopic confirmation. This study proposes a deep-learn...
Speech Production Measurement Voice Quality Dysphonia Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Pilot Projects Support Vector Machine Predictive Value of Tests Signal Processing, Computer-Assisted Acoustics Sound Spectrography Speech Acoustics Vocal Cords Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Young Adult Humans
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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...
Humans Databases, Factual Female Male Case-Control Studies Diagnosis, Computer-Assisted Support Vector Machine Predictive Value of Tests Signal Processing, Computer-Assisted Speech Production Measurement Pattern Recognition, Automated Voice Quality Edema Speech Acoustics Vocal Cord Paralysis Vocal Cords Voice Disorders
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Evolving Spiking Neural Networks for Recognition of Aged Voices.

Journal of voice : official journal of the Voice Foundation Apr 1, 2016
The aging of the voice, known as presbyphonia, is a natural process that can cause great change in vocal quality of the individual. This is a relevant problem to those people who use their voices professionally, and its early identification can help ...
Speech Acoustics Speech Production Measurement Pattern Recognition, Physiological Voice Quality Aging Middle Aged Adolescent Age Factors Signal Processing, Computer-Assisted Acoustics Sound Spectrography Female Humans Aged Neural Networks, Computer Aged, 80 and over Algorithms Young Adult Adult Male
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A neural-based vocoder implementation for evaluating cochlear implant coding strategies.

Hearing research Jan 14, 2016
Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and ref...
Time Factors Electroencephalography Signal Processing, Computer-Assisted Prosthesis Design Acoustic Stimulation Auditory Pathways Humans Auditory Threshold Cochlear Implantation Voice Quality Neural Networks, Computer Stochastic Processes Loudness Perception Computer Simulation Electric Stimulation Psychoacoustics Female Cochlear Implants Adult Persons with Hearing Disabilities Male Speech Perception Middle Aged Speech Acoustics
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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...
Male Humans Female Middle Aged Voice Disorders Principal Component Analysis Reproducibility of Results Case-Control Studies Laryngoscopy Aged Video Recording Time Factors Vibration Adult Image Interpretation, Computer-Assisted Support Vector Machine Phonation Biomechanical Phenomena Pattern Recognition, Automated Predictive Value of Tests Larynx Wavelet Analysis Voice Quality Vocal Cords
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Different Performances of Machine Learning Models to Classify Dysphonic and Non-Dysphonic Voices.

Journal of voice : official journal of the Voice Foundation May 1, 2025
OBJECTIVE: To analyze the performance of 10 different machine learning (ML) classifiers for discrimination between dysphonic and non-dysphonic voices, using a variance threshold as a method for the selection and reduction of acoustic measurements use...
Sound Spectrography Speech Acoustics Speech Production Measurement Voice Quality Dysphonia Middle Aged Case-Control Studies Predictive Value of Tests Bayes Theorem Signal Processing, Computer-Assisted Acoustics Humans Machine Learning Female Reproducibility of Results Young Adult Adult Male
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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; ...
Reproducibility of Results Adult Male Severity of Illness Index Deep Learning Time Factors Predictive Value of Tests Humans Neural Networks, Computer Female Voice Disorders Speech Production Measurement Voice Quality Signal Processing, Computer-Assisted Acoustics Observer Variation Automation Judgment Speech Acoustics
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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...
Vocal Cords Voice Disorders Humans Speech Production Measurement Databases, Factual Support Vector Machine Phonation Female Predictive Value of Tests Voice Quality Reproducibility of Results Aged Signal Processing, Computer-Assisted Dysphonia Young Adult Acoustics Adult Sound Spectrography Male Speech Acoustics Middle Aged Vocal Cord Paralysis Case-Control Studies
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A WaveNet-based model for predicting the electroglottographic signal from the acoustic voice signal.

The Journal of the Acoustical Society of America Apr 1, 2025
The electroglottographic (EGG) signal offers a non-invasive approach to analyze phonation. It is known, if not obvious, that the onset of vocal fold contacting has a substantial effect on how the vocal folds vibrate and on the quality of the voice. G...
Humans Neural Networks, Computer Speech Acoustics Vocal Cords Voice Phonation Electrodiagnosis Voice Quality Glottis Retrospective Studies Female Young Adult Adult Male Signal Processing, Computer-Assisted
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