AIMC Topic: Voice Quality

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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...
Vocal Cords Speech Production Measurement Voice Quality Dysphonia Support Vector Machine Predictive Value of Tests Signal Processing, Computer-Assisted Acoustics Sound Spectrography Speech Acoustics Humans Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Pilot Projects
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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 Speech Acoustics Diagnosis, Computer-Assisted Databases, Factual Vocal Cord Paralysis Support Vector Machine Female Vocal Cords Predictive Value of Tests Male Voice Disorders Signal Processing, Computer-Assisted Case-Control Studies Speech Production Measurement Pattern Recognition, Automated Voice Quality Edema
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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 ...
Signal Processing, Computer-Assisted Acoustics Sound Spectrography Speech Acoustics Speech Production Measurement Pattern Recognition, Physiological Voice Quality Adult Male Aging Middle Aged Adolescent Age Factors Humans Neural Networks, Computer Algorithms Female Aged Aged, 80 and over Young Adult
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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...
Middle Aged Time Factors Electroencephalography Signal Processing, Computer-Assisted Prosthesis Design Acoustic Stimulation Humans Neural Networks, Computer Speech Perception Auditory Pathways Computer Simulation Speech Acoustics Female Cochlear Implantation Auditory Threshold Adult Stochastic Processes Voice Quality Male Electric Stimulation Loudness Perception Cochlear Implants Psychoacoustics Persons with Hearing Disabilities
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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...
Principal Component Analysis Male Humans Voice Disorders Video Recording Middle Aged Female Laryngoscopy Image Interpretation, Computer-Assisted Case-Control Studies Reproducibility of Results Vibration Pattern Recognition, Automated Time Factors Aged Phonation Support Vector Machine Wavelet Analysis Adult Larynx Predictive Value of Tests Vocal Cords Biomechanical Phenomena Voice Quality
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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...
Predictive Value of Tests Bayes Theorem Signal Processing, Computer-Assisted Reproducibility of Results Acoustics Speech Production Measurement Sound Spectrography Young Adult Speech Acoustics Adult Male Humans Middle Aged Machine Learning Case-Control Studies Female Voice Quality Dysphonia
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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; ...
Judgment Speech Acoustics Voice Disorders Speech Production Measurement Voice Quality Female Reproducibility of Results Adult Male Severity of Illness Index Deep Learning Time Factors Predictive Value of Tests Humans Signal Processing, Computer-Assisted Neural Networks, Computer Acoustics Observer Variation Automation
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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...
Databases, Factual Female Reproducibility of Results Aged Young Adult Adult Humans Acoustics Sound Spectrography Speech Acoustics Vocal Cord Paralysis Vocal Cords Voice Disorders Speech Production Measurement Male Middle Aged Case-Control Studies Support Vector Machine Predictive Value of Tests Signal Processing, Computer-Assisted Phonation Voice Quality Dysphonia
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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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The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals.

The Journal of the Acoustical Society of America Mar 1, 2025
Vocal intensity is quantified by sound pressure level (SPL). The SPL can be measured by either using a sound level meter or by comparing the energy of the recorded speech signal with the energy of the recorded calibration tone of a known SPL. Neither...
Pressure Speech Acoustics Humans Speech Production Measurement Voice Quality Machine Learning Female Adult Aged Male Middle Aged Case-Control Studies Signal Processing, Computer-Assisted Sound Spectrography
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