基于改进SVM算法的元音识别模型的应用

Lingling Zhao, Kuihe Yang
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引用次数: 1

摘要

元音是来自肺部的空气不被嘴或喉咙阻挡的声音。区分不同元音的发音特征被认为决定了元音的音质。识别不同的元音类别是非常重要的。提出了一种基于改进最小二乘支持向量机(LSSVM)的元音识别模型。该模型在使用LSSVM进行元音识别时,提出了动态选择核函数参数的方法,提高了诊断的正确率。对斐波那契对称搜索算法进行了简化和改进。研究了核函数搜索区域的变化规律和最佳缩短步长。通过综合核函数搜索区域和最佳缩短步长,获得最佳模式识别效果。仿真结果表明了该元音识别模型的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Vowel Recognition Model Based on Improved SVM Algorithm
A vowel is a sound where air coming from the lungs is not blocked by the mouth or throat. The articulatory features that distinguish different vowel sounds are said to determine the vowel's quality. It is very important to recognize different vowel classes. A vowel recognition model based on improved least squares support vector machine (LSSVM) is presented. In the model, when the LSSVM is used in vowel recognition, it is presented to choose parameter of kernel function on dynamic, which enhances preciseness rate of diagnosis. The Fibonacci symmetry searching algorithm is simplified and improved. The changing rule of kernel function searching region and best shortening step is studied. The best pattern recognition results are obtained by means of synthesizing kernel function searching region and best shortening step. The simulation results show the validity of the vowel recognition model.
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