比例优势逻辑回归优化嗓音障碍指数算法

Proportional Dominance Logistic Regression Optimized Voice Disorder Index Algorithm

针对嗓音障碍指数在提取传统声学特征参数时,缺少对非传统声学特征参数的分析优化问题,本文提出一种基于有序比例优势逻辑回归的优化嗓音障碍指数算法。首先,提取频谱平坦度并与嗓音障碍指数进行相关性分析;其次,运用比例几率逻辑回归方法,得到新的嗓音障碍指数方程;最后,对数据库中所取样本的本文优化算法指数和传统嗓音障碍指数进行对比分析。本文优化算法拓宽了DSI的取值范围。将本文算法应用于嗓音障碍分级中,实验结果表明该算法能够有效地确定嗓音障碍指数数值并能迅速得到良好的分类结果。

To address the problem that the voice impairment index lacks the analysis and optimization of non-traditional acoustic feature parameters when extracting traditional acoustic feature parameters,this paper proposes an algorithm to optimize the voice impairment index based on ordered proportional dominance logistic regression.Firstly,the spectral flatness is extracted and cor⁃related with the voice impairment index.Secondly,the new equation of voice disorder index is obtained by applying the propor⁃tional odds logistic regression method.Finally,a comparison is made between the DSI and the traditional voice disorder index for the samples taken from the database.This paper optimizes the algorithm to broaden the range of values for DSI.The algorithm in this paper is applied to the classification of voice disorders.The experimental results show that the algorithm can effectively deter⁃mine the values of DSI and obtain good classification results quickly.