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Estimating area function of the vocal tract from formants using a sensitivity function and least-squares

机译:使用敏感度函数和最小二乘估计共振峰的声道面积函数

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References(23) Cited-By(1) We present methods for estimating the cross-sectional area function of the vocal tract from formant frequencies. They extend the work of Story (J. Acoust. Soc. Am., 119, 715–718, 1996) based on a sensitivity function representing the change in the formant frequency due to a perturbation of the cross-sectional area. In Method I, the area function is estimated through an iterative procedure that uses the sensitivity function as the basis function to optimize the area function that produces the target frequencies. In Method II, a mode function linearly expands the area function. The estimation is performed by optimizing the value of each mode coefficient, where the sensitivity function is used as a constraint in the optimization. As a specific feature, the summing weight of sensitivity functions in Method I and mode functions in Method II is determined by minimizing an objective function representing the frequency error of every formant. By using existing area function data for English vowels, we compare the performance of each method with respect to the estimation accuracy and convergence speed. The results show that our methods can effectively reduce degrees of freedom of the area function and quickly obtain the optimal solution with fair accuracy.
机译:参考文献(23)Cited-By(1)我们提出了从共振峰频率估算声道横截面积函数的方法。他们基于表示由横截面积的扰动引起的共振峰频率变化的灵敏度函数,扩展了Story(J. Acoust。Soc。Am。,119,715-718,1996)的工作。在方法I中,面积函数是通过迭代过程估算的,该迭代过程使用灵敏度函数作为基础函数来优化产生目标频率的面积函数。在方法II中,模式函数线性扩展面积函数。通过优化每个模式系数的值来执行估算,其中灵敏度函数用作优化中的约束。作为一个特定特征,方法I中灵敏度函数和方法II中模式函数的总权重是通过最小化表示每个共振峰频率误差的目标函数来确定的。通过使用现有的英语元音区域函数数据,我们就估计精度和收敛速度比较了每种方法的性能。结果表明,我们的方法可以有效地降低面积函数的自由度,并以合理的精度快速获得最优解。

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