AIMC Topic: Voice Quality

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Pathological Voice Detection Based on Phase Reconstitution and Convolutional Neural Network.

Journal of voice : official journal of the Voice Foundation Oct 21, 2022
The nonlinear dynamic features can effectively describe the acoustic characteristics of normal and pathological voice. In this paper, the phase space reconstruction and convolution neural network are used to classify the normal and pathological voice...
Female Reproducibility of Results Male Case-Control Studies Convolutional Neural Networks Humans Neural Networks, Computer Databases, Factual Nonlinear Dynamics Speech Acoustics Vocal Cord Paralysis Voice Disorders Speech Production Measurement Voice Quality Time Factors Predictive Value of Tests Signal Processing, Computer-Assisted Acoustics Sound Spectrography
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Deep-Learning-Based Representation of Vocal Fold Dynamics in Adductor Spasmodic Dysphonia during Connected Speech in High-Speed Videoendoscopy.

Journal of voice : official journal of the Voice Foundation Sep 23, 2022
OBJECTIVE: Adductor spasmodic dysphonia (AdSD) is a neurogenic dystonia, which causes spasms of the laryngeal muscles. This disorder mainly affects production of connected speech. To understand how AdSD affects vocal fold (VF) movements and hence, th...
Voice Quality Dysphonia Adult Deep Learning Vocal Cords Predictive Value of Tests Biomechanical Phenomena Laryngoscopy Video Recording Male Vibration Image Interpretation, Computer-Assisted Middle Aged Speech Production Measurement Humans Speech Acoustics Case-Control Studies Female Phonation Reproducibility of Results
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Performance of Acoustic Measures for the Discrimination Among Healthy, Rough, Breathy, and Strained Voices Using the Feedforward Neural Network.

Journal of voice : official journal of the Voice Foundation Aug 23, 2022
OBJECTIVE: To identify and evaluate the best set of acoustic measures to discriminate among healthy, rough, breathy, and strained voices.
Reproducibility of Results Aged Young Adult Adult Male Humans Neural Networks, Computer Algorithms Female Acoustics Sound Spectrography Speech Acoustics Voice Disorders Speech Production Measurement Middle Aged Case-Control Studies Adolescent Predictive Value of Tests Signal Processing, Computer-Assisted Voice Quality Feedforward Neural Networks
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The Effect of the MFCC Frame Length in Automatic Voice Pathology Detection.

Journal of voice : official journal of the Voice Foundation Apr 27, 2022
Automatic voice pathology detection is a research topic, which has gained increasing interest recently. Although methods based on deep learning are becoming popular, the classical pipeline systems based on a two-stage architecture consisting of a fea...
Dysphonia Support Vector Machine Predictive Value of Tests Signal Processing, Computer-Assisted Acoustics Sound Spectrography Automation Speech Acoustics Voice Disorders Speech Production Measurement Voice Quality Humans Databases, Factual Reproducibility of Results
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Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.

Journal of voice : official journal of the Voice Foundation Nov 26, 2021
Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effe...
Phonation Voice Quality Cough COVID-19 Testing COVID-19 Speech Acoustics Humans Female Voice Disorders Machine Learning Adult Reproducibility of Results Speech Production Measurement Male SARS-CoV-2 Middle Aged Aged Case-Control Studies Predictive Value of Tests
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Deep Learning for Voice Gender Identification: Proof-of-concept for Gender-Affirming Voice Care.

The Laryngoscope Nov 21, 2020
OBJECTIVES/HYPOTHESIS: The need for gender-affirming voice care has been increasing in the transgender population in the last decade. Currently, objective treatment outcome measurements are lacking to assess the success of these interventions. This s...
Humans Retrospective Studies Female Adult Male Deep Learning Treatment Outcome Audiometry Voice Quality Gender-Affirming Procedures Sex Factors Datasets as Topic Transgender Persons Proof of Concept Study Speech Perception
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Machine learning based identification of relevant parameters for functional voice disorders derived from endoscopic high-speed recordings.

Scientific reports Jun 29, 2020
In voice research and clinical assessment, many objective parameters are in use. However, there is no commonly used set of parameters that reflect certain voice disorders, such as functional dysphonia (FD); i.e. disorders with no visible anatomical c...
Voice Disorders Laryngoscopy Voice Quality Machine Learning Female Endoscopy Male Age Factors Humans
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Discrimination of "hot potato voice" caused by upper airway obstruction utilizing a support vector machine.

The Laryngoscope Nov 28, 2018
OBJECTIVES/HYPOTHESIS: "Hot potato voice" (HPV) is a thick, muffled voice caused by pharyngeal or laryngeal diseases characterized by severe upper airway obstruction, including acute epiglottitis and peritonsillitis. To develop a method for determini...
Voice Disorders Phonation Voice Quality Airway Obstruction Support Vector Machine Signal Processing, Computer-Assisted Sound Spectrography Pattern Recognition, Automated Voice Humans
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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...
Reproducibility of Results Diagnosis, Computer-Assisted Humans Wavelet Analysis Predictive Value of Tests Machine Learning Voice Disorders Acoustics Larynx Pattern Recognition, Automated 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.
Laryngeal Neoplasms Voice Quality Glottis Age Factors Supervised Machine Learning Aged Sex Factors Humans Symptom Assessment Adult Neural Networks, Computer Smoking Wounds and Injuries Male Alcohol Drinking Algorithms Demography Middle Aged Retrospective Studies Vocal Cord Paralysis Severity of Illness Index Female Voice Disorders
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