AIMC Topic: Speech Production Measurement

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Real-Time Control of an Articulatory-Based Speech Synthesizer for Brain Computer Interfaces.

PLoS computational biology Nov 23, 2016
Restoring natural speech in paralyzed and aphasic people could be achieved using a Brain-Computer Interface (BCI) controlling a speech synthesizer in real-time. To reach this goal, a prerequisite is to develop a speech synthesizer producing intelligi...
Communication Devices for People with Disabilities Speech Production Measurement Sound Spectrography Humans Brain-Computer Interfaces Neural Networks, Computer Speech Intelligibility Computer Systems Phonetics Biofeedback, Psychology Speech Acoustics
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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...
Predictive Value of Tests Signal Processing, Computer-Assisted Pattern Recognition, Automated Edema Speech Acoustics Vocal Cord Paralysis Vocal Cords Voice Disorders Speech Production Measurement Voice Quality Female Male Case-Control Studies Diagnosis, Computer-Assisted Support Vector Machine Humans Databases, Factual
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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 ...
Pattern Recognition, Physiological Voice Quality Signal Processing, Computer-Assisted Female Acoustics Male Aged Sound Spectrography Aging Aged, 80 and over Speech Acoustics Humans Middle Aged Adolescent Age Factors Neural Networks, Computer Algorithms Young Adult Adult Speech Production Measurement
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Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation.

International journal of neural systems Mar 29, 2016
This paper presents a neural system-based technique for segmenting short impaired speech utterances into silent, unvoiced, and voiced sections. Moreover, the proposed technique identifies those points of the (voiced) speech where the spectrum becomes...
Speech Therapy Humans Male Neural Networks, Computer Speech Female Support Vector Machine Speech Production Measurement Speech Disorders
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Minimum Entropy Rate Simplification of Stochastic Processes.

IEEE transactions on pattern analysis and machine intelligence Feb 23, 2016
We propose minimum entropy rate simplification (MERS), an information-theoretic, parameterization-independent framework for simplifying generative models of stochastic processes. Applications include improving model quality for sampling tasks by conc...
Entropy Speech Production Measurement Animals Humans Models, Statistical Machine Learning Models, Biological Algorithms Sound Spectrography Computer Simulation Pattern Recognition, Automated
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Geometry of orofacial neuromuscular signals: speech articulation decoding using surface electromyography.

Journal of neural engineering Jul 2, 2025
In this article, we present data and methods for decoding speech articulations using surface electromyogram (EMG) signals. EMG-based speech neuroprostheses offer a promising approach for restoring audible speech in individuals who have lost the abili...
Middle Aged Speech Electromyography Speech Production Measurement Facial Muscles Humans Female Young Adult Adult Male
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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...
Humans Machine Learning Female Reproducibility of Results Sound Spectrography Speech Acoustics Speech Production Measurement Case-Control Studies Voice Quality Young Adult Predictive Value of Tests Dysphonia Adult Bayes Theorem Male Signal Processing, Computer-Assisted Middle Aged Acoustics
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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; ...
Speech Production Measurement Voice Quality Observer Variation Automation Judgment Speech Acoustics Voice Disorders Time Factors Predictive Value of Tests Signal Processing, Computer-Assisted Acoustics Humans Neural Networks, Computer Female Reproducibility of Results Adult Male Severity of Illness Index Deep Learning
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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...
Signal Processing, Computer-Assisted Acoustics Sound Spectrography Speech Acoustics Vocal Cord Paralysis Middle Aged Case-Control Studies Support Vector Machine Predictive Value of Tests Dysphonia Vocal Cords Voice Disorders Speech Production Measurement Phonation Voice Quality Humans Databases, Factual Female Reproducibility of Results Aged Young Adult Adult Male
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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...
Sound Spectrography Pressure Speech Acoustics Speech Production Measurement Voice Quality Male Middle Aged Case-Control Studies Signal Processing, Computer-Assisted Humans Machine Learning Female Aged Adult
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