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A new procedure for automatic fitting of the basilar-membrane input-output function to individual behavioral data.

机译:将基底膜输入输出功能自动拟合到个体行为数据的新程序。

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摘要

The basilar membrane input-output function (BM I/O) in a healthy cochlea is highly nonlinear. One of the consequences of sensorineural hearing loss (SNHL) is a partial or full loss of this nonlinearity. Behavioral estimates of the individual BM I/O can be useful for modeling the impaired auditory system and, potentially, for clinical diagnostics. Computational algorithms are available that mimic the functioning of the nonlinear cochlear processing. One such algorithm is the dual resonance non-linear (DRNL) filterbank [6]. Its parameters can be modified to account for individual hearing loss, e.g., based on behavioral, temporal masking curves (TMC) data. This approach was used within the framework of the computational auditory signal-processing and perception (CASP) model to account for various aspects of SNHL [4].However, due to the computational complexity, on-line fitting of the DRNL parameters is difficult.Until recently, the parameters were manually adjusted and the fitting process was indirect. A new approach is described here, based on a search through a lookup table of pre-computed filterbankinput-output functions. The aim of this approach is to provide a fast, stable, and more objective fitting procedure.
机译:健康的耳蜗中的基底膜输入输出功能(BM I / O)是高度非线性的。感音神经性听力损失(SNHL)的后果之一是这种非线性的部分或全部丧失。单个BM I / O的行为估计可用于对受损的听觉系统进行建模,并可能用于临床诊断。可以使用计算算法来模拟非线性耳蜗处理的功能。一种这样的算法是双谐振非线性(DRNL)滤波器组[6]。可以例如基于行为,时间掩蔽曲线(TMC)数据来修改其参数以解决个体听力损失。这种方法在计算听觉信号处理和感知(CASP)模型的框架内使用,以解决SNHL的各个方面[4]。但是,由于计算复杂,DRNL参数的在线拟合很困难。直到最近,这些参数都是手动调整的,并且拟合过程是间接的。在此基于通过对预先计算的filterbankinput-output函数的查找表的搜索来描述一种新方法。该方法的目的是提供一种快速,稳定和客观的拟合过程。

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