Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method
Introduction. In vocal production models employing spring-mass-damper frameworks, precision in determining damping coefficients that align with physiological vocal fold characteristics is crucial, accounting for potential variations in the representation of viscosity-elasticity properties. Object...
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Format: | Article |
Language: | Spanish |
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Fundación Universitaria María Cano
2024-01-01
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Series: | Revista de Investigación e Innovación en Ciencias de la Salud |
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Online Access: | https://riics.info/index.php/RCMC/article/view/234 |
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author | Carlos-Alberto Calvache-Mora Leonardo Soláque Alexandra Velasco Lina Peñuela |
author_facet | Carlos-Alberto Calvache-Mora Leonardo Soláque Alexandra Velasco Lina Peñuela |
author_sort | Carlos-Alberto Calvache-Mora |
collection | DOAJ |
description |
Introduction. In vocal production models employing spring-mass-damper frameworks, precision in determining damping coefficients that align with physiological vocal fold characteristics is crucial, accounting for potential variations in the representation of viscosity-elasticity properties.
Objective. This study aims to conduct a parametric fitting of a vocal production model based on a mass-spring-damper system incorporating subglottic pressure interaction, with the purpose of accurately modeling the collision forces exerted by vocal folds during phonation.
Method. A metaheuristic search algorithm was employed for parametric synthesis. The algorithm was applied to elasticity coefficients c1 and c2, as well as damping coefficients ε1 and ε2, which directly correlate with the mass matrices of the model. This facilitates the adjustment of fold composition to achieve desired physiological behavior.
Results. The vocal system's behavior for each simulation cycle was compared to a predefined standard under normal conditions. The algorithm determined the simulation endpoint by evaluating discrepancies between key features of the obtained signals and the desired ones.
Conclusion. Parametric fitting enabled the approximation of physiological vocal production behavior, providing estimates of the impact forces experienced by vocal folds during phonation.
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first_indexed | 2024-03-08T09:42:55Z |
format | Article |
id | doaj.art-97cd89aa8396416bac61371f2bbe3fed |
institution | Directory Open Access Journal |
issn | 2665-2056 |
language | Spanish |
last_indexed | 2024-03-08T09:42:55Z |
publishDate | 2024-01-01 |
publisher | Fundación Universitaria María Cano |
record_format | Article |
series | Revista de Investigación e Innovación en Ciencias de la Salud |
spelling | doaj.art-97cd89aa8396416bac61371f2bbe3fed2024-01-30T03:44:42ZspaFundación Universitaria María CanoRevista de Investigación e Innovación en Ciencias de la Salud2665-20562024-01-016110.46634/riics.234Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic MethodCarlos-Alberto Calvache-Mora0Leonardo Soláque1Alexandra Velasco2Lina Peñuela3Department of Mechatronics Engineering; Universidad Militar Nueva Granada; Bogotá, Colombia. / Vocology Research; Vocology Center; Bogotá; Colombia. / Communication Science and Disorders; Corporación Universitaria Iberoamericana; Bogotá; Colombia.Department of Mechatronics Engineering; Universidad Militar Nueva Granada; Bogotá, ColombiaDepartment of Mechatronics Engineering; Universidad Militar Nueva Granada; Bogotá, ColombiaDepartment of Mechatronics Engineering; Universidad Militar Nueva Granada; Bogotá, Colombia Introduction. In vocal production models employing spring-mass-damper frameworks, precision in determining damping coefficients that align with physiological vocal fold characteristics is crucial, accounting for potential variations in the representation of viscosity-elasticity properties. Objective. This study aims to conduct a parametric fitting of a vocal production model based on a mass-spring-damper system incorporating subglottic pressure interaction, with the purpose of accurately modeling the collision forces exerted by vocal folds during phonation. Method. A metaheuristic search algorithm was employed for parametric synthesis. The algorithm was applied to elasticity coefficients c1 and c2, as well as damping coefficients ε1 and ε2, which directly correlate with the mass matrices of the model. This facilitates the adjustment of fold composition to achieve desired physiological behavior. Results. The vocal system's behavior for each simulation cycle was compared to a predefined standard under normal conditions. The algorithm determined the simulation endpoint by evaluating discrepancies between key features of the obtained signals and the desired ones. Conclusion. Parametric fitting enabled the approximation of physiological vocal production behavior, providing estimates of the impact forces experienced by vocal folds during phonation. https://riics.info/index.php/RCMC/article/view/234Vocal modelimpact stressmetaheuristic methodsfine-tunning |
spellingShingle | Carlos-Alberto Calvache-Mora Leonardo Soláque Alexandra Velasco Lina Peñuela Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method Revista de Investigación e Innovación en Ciencias de la Salud Vocal model impact stress metaheuristic methods fine-tunning |
title | Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method |
title_full | Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method |
title_fullStr | Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method |
title_full_unstemmed | Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method |
title_short | Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method |
title_sort | fine tuning of a voice production model to estimate impact stress using a metaheuristic method |
topic | Vocal model impact stress metaheuristic methods fine-tunning |
url | https://riics.info/index.php/RCMC/article/view/234 |
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