声门闭合合成声带模型的优化。

Cassandra J Taylor, Scott L Thomson
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引用次数: 2

摘要

合成的,人类声带的自振荡模型被用来研究复杂的和相互关联的流动,结构,以及声音产生的声学方面。在每个周期中,声带通常会发生碰撞,从而造成短暂的声门关闭,这对流动、声学和运动相关的结果具有重要意义。然而,许多先前的合成模型受到振动时声门关闭不完全的限制。在这项研究中,将低保真度、二维、多层声带流诱发振动的有限元模型与定制的遗传算法优化代码相结合,以确定几何和材料特征,这些特征将产生生理上真实的频率和闭合商值。优化过程得到的计算模型具有良好的频率和闭商特性。在频率和闭商之间观察到一种权衡。根据模拟结果,合成了具有几何和材料特性的自振荡声带模型,并对其启动压力、振荡频率和闭合商进行了测试。该模型成功地在真实频率下振动,并表现出非零闭商。本研究中描述的方法为使用各向同性硅树脂材料制造合成模型提供了潜在的方向,这些材料可以设计成以生理真实的频率和封闭商值振动。结果还显示了一种低保真模型优化方法的潜力,可用于调整合成声带模型的特定振动结果特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Optimization of Synthetic Vocal Fold Models for Glottal Closure.

Synthetic, self-oscillating models of the human vocal folds are used to study the complex and inter-related flow, structure, and acoustical aspects of voice production. The vocal folds typically collide during each cycle, thereby creating a brief period of glottal closure that has important implications for flow, acoustic, and motion-related outcomes. Many previous synthetic models, however, have been limited by incomplete glottal closure during vibration. In this study, a low-fidelity, two-dimensional, multilayer finite element model of vocal fold flow-induced vibration was coupled with a custom genetic algorithm optimization code to determine geometric and material characteristics that would be expected to yield physiologically-realistic frequency and closed quotient values. The optimization process yielded computational models that vibrated with favorable frequency and closed quotient characteristics. A tradeoff was observed between frequency and closed quotient. A synthetic, self-oscillating vocal fold model with geometric and material properties informed by the simulation outcomes was fabricated and tested for onset pressure, oscillation frequency, and closed quotient. The synthetic model successfully vibrated at a realistic frequency and exhibited a nonzero closed quotient. The methodology described in this study provides potential direction for fabricating synthetic models using isotropic silicone materials that can be designed to vibrate with physiologically-realistic frequencies and closed quotient values. The results also show the potential for a low-fidelity model optimization approach to be used to tune synthetic vocal fold model characteristics for specific vibratory outcomes.

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