AIMC Topic: Speech Production Measurement

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Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.

International journal of chronic obstructive pulmonary disease Jan 20, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Pulmonary Disease, Chronic Obstructive Male Middle Aged Disease Progression Lung Prospective Studies Prognosis Female Reproducibility of Results Aged Functional Status Respiratory Function Tests Speech Acoustics Speech Production Measurement Voice Quality Severity of Illness Index Speech Time Factors Support Vector Machine Predictive Value of Tests Humans
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Computing nasalance with MFCCs and Convolutional Neural Networks.

PloS one Dec 31, 2024
Nasalance is a valuable clinical biomarker for hypernasality. It is computed as the ratio of acoustic energy emitted through the nose to the total energy emitted through the mouth and nose (eNasalance). A new approach is proposed to compute nasalance...
Speech Chile Speech Acoustics Speech Production Measurement Nose Neural Networks, Computer Language Female Adult Male Costa Rica Humans
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Artificial Intelligence-Assisted Speech Therapy for /ɹ/: A Single-Case Experimental Study.

American journal of speech-language pathology Aug 22, 2024
PURPOSE: This feasibility trial describes changes in rhotic production in residual speech sound disorder following ten 40-min sessions including artificial intelligence (AI)-assisted motor-based intervention with ChainingAI, a version of Speech Motor...
Male Adolescent Child Treatment Outcome Feasibility Studies Humans Artificial Intelligence Female Young Adult Speech Sound Disorder Therapy, Computer-Assisted Phonetics Speech Production Measurement Speech Therapy
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Accuracy of Speech Sound Analysis: Comparison of an Automatic Artificial Intelligence Algorithm With Clinician Assessment.

Journal of speech, language, and hearing research : JSLHR Aug 22, 2024
PURPOSE: Automatic speech analysis (ASA) and automatic speech recognition systems are increasingly being used in the treatment of speech sound disorders (SSDs). When utilized as a home practice tool or in the absence of the clinician, the ASA system ...
Reproducibility of Results Speech Recognition Software Humans Male Phonetics Artificial Intelligence Adolescent Speech Production Measurement Algorithms Child, Preschool Speech Sound Disorder Female Child
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TranStutter: A Convolution-Free Transformer-Based Deep Learning Method to Classify Stuttered Speech Using 2D Mel-Spectrogram Visualization and Attention-Based Feature Representation.

Sensors (Basel, Switzerland) Sep 22, 2023
Stuttering, a prevalent neurodevelopmental disorder, profoundly affects fluent speech, causing involuntary interruptions and recurrent sound patterns. This study addresses the critical need for the accurate classification of stuttering types. The res...
Humans Deep Learning Speech Stuttering Speech Production Measurement Speech Disorders
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Recognition of the Effect of Vocal Exercises by Fuzzy Triangular Naive Bayes, a Machine Learning Classifier: A Preliminary Analysis.

Journal of voice : official journal of the Voice Foundation Nov 11, 2022
OBJECTIVES: Machine learning (ML) methods allow the development of expert systems for pattern recognition and predictive analysis of intervention outcomes. It has been used in Voice Sciences, mainly to discriminate between healthy and dysphonic voice...
Voice Quality Dysphonia Voice Training Signal Processing, Computer-Assisted Acoustics Humans Speech Perception Machine Learning Speech Acoustics Treatment Outcome Female Speech Production Measurement Fuzzy Logic Reproducibility of Results Predictive Value of Tests Young Adult Bayes Theorem Adult Middle Aged Case-Control Studies
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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...
Humans Neural Networks, Computer Databases, Factual Female Reproducibility of Results Male Case-Control Studies Speech Production Measurement Voice Quality Sound Spectrography Nonlinear Dynamics Convolutional Neural Networks Speech Acoustics Time Factors Vocal Cord Paralysis Predictive Value of Tests Voice Disorders Signal Processing, Computer-Assisted Acoustics
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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...
Reproducibility of Results Adult Biomechanical Phenomena Male Phonation Middle Aged Voice Quality Speech Acoustics Dysphonia Humans Vocal Cords Female Case-Control Studies Laryngoscopy Vibration Deep Learning Speech Production Measurement Predictive Value of Tests Video Recording Image Interpretation, Computer-Assisted
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Deep learning in automatic detection of dysphonia: Comparing acoustic features and developing a generalizable framework.

International journal of language & communication disorders Sep 18, 2022
BACKGROUND: Auditory-perceptual assessment of voice is a subjective procedure. Artificial intelligence with deep learning (DL) may improve the consistency and accessibility of this task. It is unclear how a DL model performs on different acoustic fea...
Speech Acoustics Artificial Intelligence Speech Production Measurement Retrospective Studies Dysphonia Reproducibility of Results Humans Deep Learning Acoustics
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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.
Voice Quality Feedforward Neural Networks Middle Aged Reproducibility of Results Acoustics Humans Case-Control Studies Aged Sound Spectrography Neural Networks, Computer Adolescent Young Adult Speech Acoustics Algorithms Predictive Value of Tests Adult Voice Disorders Female Signal Processing, Computer-Assisted Male Speech Production Measurement
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