Speech signal filtration using double-density dual-tree complex wavelet transform

被引：4
|
作者：
Yasin, A. S. [1 ,2 ]
Pavlova, O. N. [1 ]
Pavlov, A. N. [1 ,3 ,4 ]
机构：
[1] Saratov NG Chernyshevskii State Univ, Saratov 410012, Russia
[2] Univ Technol Baghdad, Baghdad, Iraq
[3] Yuri Gagarin State Tech Univ Saratov, Saratov 410054, Russia
[4] Kotelnikov Inst Radio Engn & Elect, Saratov Branch, Saratov 410019, Russia
来源：
TECHNICAL PHYSICS LETTERS | 2016年 / 42卷 / 08期
基金：
俄罗斯科学基金会;
关键词：
D O I：
10.1134/S1063785016080290
中图分类号：
O59 [应用物理学];
学科分类号：
摘要：
We consider the task of increasing the quality of speech signal cleaning from additive noise by means of double-density dual-tree complex wavelet transform (DDCWT) as compared to the standard method of wavelet filtration based on a multiscale analysis using discrete wavelet transform (DWT) with real basis set functions such as Daubechies wavelets. It is shown that the use of DDCWT instead of DWT provides a significant increase in the mean opinion score (MOS) rating at a high additive noise and makes it possible to reduce the number of expansion levels for the subsequent correction of wavelet coefficients.
引用
收藏
页码：865 / 867
页数：3
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