Department of Otolaryngology, New York University School of Medicine, New York, New York 10016, USA.
J Acoust Soc Am. 2010 Feb;127(2):1069-83. doi: 10.1121/1.3277215.
A simple mathematical model is presented that predicts vowel identification by cochlear implant users based on these listeners' resolving power for the mean locations of first, second, and/or third formant energies along the implanted electrode array. This psychophysically based model provides hypotheses about the mechanism cochlear implant users employ to encode and process the input auditory signal to extract information relevant for identifying steady-state vowels. Using one free parameter, the model predicts most of the patterns of vowel confusions made by users of different cochlear implant devices and stimulation strategies, and who show widely different levels of speech perception (from near chance to near perfect). Furthermore, the model can predict results from the literature, such as Skinner, et al. [(1995). Ann. Otol. Rhinol. Laryngol. 104, 307-311] frequency mapping study, and the general trend in the vowel results of Zeng and Galvin's [(1999). Ear Hear. 20, 60-74] studies of output electrical dynamic range reduction. The implementation of the model presented here is specific to vowel identification by cochlear implant users, but the framework of the model is more general. Computational models such as the one presented here can be useful for advancing knowledge about speech perception in hearing impaired populations, and for providing a guide for clinical research and clinical practice.
本文提出了一个简单的数学模型，用于预测人工耳蜗使用者的元音识别能力，该模型基于这些听者对第一、第二和/或第三共振峰能量在植入电极阵列上的平均位置的分辨力。该基于心理物理的模型提供了关于人工耳蜗使用者用来编码和处理输入听觉信号以提取与识别稳态元音相关的信息的机制的假设。使用一个自由参数，该模型预测了不同人工耳蜗设备和刺激策略的使用者以及表现出广泛不同的言语感知水平（从近乎偶然到近乎完美）的使用者的大部分元音混淆模式。此外，该模型还可以预测文献中的结果，例如 Skinner 等人的[(1995)。耳鼻喉科与头颈部外科学杂志 104, 307-311]频率映射研究，以及 Zeng 和 Galvin 的[(1999)。听力研究 20, 60-74]研究中输出电动态范围减小的元音结果的总体趋势。本文提出的模型的实现特定于人工耳蜗使用者的元音识别，但模型的框架更具普遍性。这样的计算模型可以有助于深入了解听力受损人群的言语感知，并为临床研究和临床实践提供指导。
