SciELO - Scientific Electronic Library Online

 
vol.6 número1Trastorno de la voz, estrés laboral y COVID-19 en profesores: repercusiones en tiempos de pandemiaDetrás de los auriculares: precisión predictiva de las medidas de resultados informadas por el paciente para los síntomas de voz en call centers índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


Revista de investigación e innovación en ciencias de la salud

versión On-line ISSN 2665-2056

Resumen

CALVACHE-MORA, Carlos-Alberto; SOLAQUE, Leonardo; VELASCO, Alexandra  y  PENUELA, Lina. Fine-Tuning of a Voice Production Model to Estimate Impact Stress Using a Metaheuristic Method. Rev. Investig. Innov. Cienc. Salud [online]. 2024, vol.6, n.1, pp.24-43.  Epub 08-Ene-2024. ISSN 2665-2056.  https://doi.org/10.46634/riics.234.

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.

Palabras clave : Vocal model; impact stress; metaheuristic methods; fine-tunning.

        · resumen en Español     · texto en Español     · Español ( pdf )