Applying the wavelet transform for the analysis of normal and pathological voices

被引：0

作者：

Jimenez, Carlos ^{[1
]}

Diaz, Jose A. ^{[1
]}

Del Pino, Paulino ^{[1
]}

Rothman, Howard ^{[2
]}

机构：

[1] Univ Carabobo, Fac Ingn, Escuela Ingn Elect, Valencia, Venezuela

[2] Univ Florida, Dept Elect & Comp Engn, Gainesville, FL 32611 USA

来源：

INGENIERIA UC | 2008年 / 15卷 / 01期

关键词：

Wavelet; speech; signal-to-noise-ratio; multi-resolution; stationary signal;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The wavelet transform db15, with a decomposition level of 10, was used in this research in order to filter voice signals and extract some parameters that would allow us to determine whether the voice signal is a healthy one or if it has some pathology. The signal-to-noise ratio of voice signals corresponding to a sustained "a", which were classified as normal or pathological by an expert in the area of speech processing, was plotted and tabulated. It was observed that for normal voices the average signal-to-noise-ratio was higher than that for pathological voices, the maximum value of the signal-to-noise-ratio was higher, and the variance of the signal-to-noise-ratio curve was lower.

引用

页码：7 / 13

页数：7

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