利用2型模糊神经网络理解元音听觉感知的生物学基础

Mousumi Laha, A. Konar, P. Rakshit, S. Chaki, A. Nagar
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引用次数: 2

摘要

人类大脑的颞叶负责低水平的声音感知,而前额叶在声音信息的解释中起着积极的作用。本文介绍了一种新的方法来理解大脑颞叶和前额叶在解释元音时的相互关系。通过两种方法确定其相互关系。第一种方法是计算两个脑叶的直接大脑信号之间的相关性。相关系数越高,激活脑叶之间的相关性越好。第二种方法旨在开发颞叶和前额叶大脑激活之间的特征级映射。第二种方法的动机在于,无论大脑信号的日变化如何,研究相同元音音频刺激收敛后习得的神经权重的一致性。虽然任何传统的映射函数都可以用来进行颞叶到前额叶的映射,但我们使用了2型模糊神经网络来实现这一目的。实验证实,所提出的2型模糊神经网络的权重收敛速度快于1型模糊神经网络和反向传播神经网络。权重的快速收敛表明,所提出的2型模糊神经网络比其他网络具有更好的音频感知能力。这项工作有望在听觉感知能力障碍的早期检测中找到应用,通常被称为阅读障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding the Biological Underpinning of Auditory Perception for Vowel Sounds Using a Type-2 Fuzzy Neural Network
The temporal lobe in the human brain is responsible for low-level audio perception, whereas the pre-frontal lobe takes active role in interpreting the audio information. This paper introduces a novel approach to understand the interrelation between the temporal and the pre-frontal lobes of the brain in interpreting vowel sounds. The inter-relation is ascertained by two approaches. The first approach computes correlation measure between the direct brain signals of the said two lobes. The higher the correlation coefficient, the better is the interrelation between the activated lobes. The second approach aims at developing a feature-level mapping between the temporal and the prefrontal lobe brain activations. The motivation of the second approach lies in examining the uniformity in the learnt neural weights after convergence for the same vowel audio stimulus irrespective of the diurnal variations in the brain signals. Although any traditional mapping functions could be utilized to undertake the temporal to prefrontal mapping, we used a type-2 fuzzy neural network to serve the purpose. Experiments undertaken confirm that the weights of the proposed type-2 fuzzy neural net converges faster than its type-1 counterpart and back-propagation neural network. The faster convergence of weights represent that the proposed type-2 fuzzy neural network captures better audio perceptual ability than the rest. The proposed work is expected to find applications in the early detection of disorder in auditory perceptual-ability, usually referred to as Dyslexia.
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