Support vector machines and wavelets for voice disorder sorting

被引：0
|
作者：
Guido, Rodrigo Capobianco [1 ]
Pereira, Jose Carlos [1 ]
Fonseca, Everthon Silva [1 ]
Maciel, Carlos Dias [1 ]
Vieira, Lucimar Sasso [1 ]
Guilerme, Fabricio Lopes Sanchez Marcio Borges A. [1 ]
Barbon, Silvio, Jr. [1 ]
机构：
[1] Univ Sao Paulo, Dept Phys & Informat, Inst Phys Sao Carlos, BR-13560970 Sao Carlos, SP, Brazil
来源：
PROCEEDINGS OF THE THIRTY-EIGHTH SOUTHEASTERN SYMPOSIUM ON SYSTEM THEORY | 2004年
关键词：
discrete wavelet transform; time-frequency analysis; voice disorders sorting; support vector machines;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We present an algorithm to distinguish between pathological and normal human voice signals based on discrete wavelet transforms (DWT) and Support Vector Machines (SVM). The former is used for time-frequency analysis and provides quantitative evaluation of signal characteristics. The latter is used for the final classification. The technique leads to an adequate larynx pathology classifier with over 95% of classification accuracy.
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页码：434 / 438
页数：5
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