SciELO - Scientific Electronic Library Online

 
vol.6 número1Voice Disorder, Job Stress, and COVID-19 in Teachers: Impacts in Times of PandemicBehind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Não possue artigos similaresSimilares em SciELO
  • Em processo de indexaçãoSimilares em Google

Compartilhar


Revista de investigación e innovación en ciencias de la salud

versão On-line ISSN 2665-2056

Resumo

CALVACHE-MORA, Carlos-Alberto; SOLAQUE, Leonardo; VELASCO, Alexandra  e  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-Jan-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.

Palavras-chave : Vocal model; impact stress; metaheuristic methods; fine-tunning.

        · resumo em Espanhol     · texto em Espanhol     · Espanhol ( pdf )