Threshold Filtering for Phoneme Pronunciation Signals Based on FrFT

被引：6

作者：

Fan, Zhenyan ^{[1
]}

Yu, Jun ^{[1
]}

Li, Zhongxiao ^{[1
]}

Zhuang, Xiaodong ^{[1
]}

Mastorakis, Nikos E. ^{[2
]}

机构：

[1] Qingdao Univ, Elect Informat Coll, Qingdao, Peoples R China

[2] Tech Univ Sofia, English Language Fac Engn, Sofia, Bulgaria

来源：

2018 2ND EUROPEAN CONFERENCE ON ELECTRICAL ENGINEERING AND COMPUTER SCIENCE (EECS 2018) | 2018年

基金：

美国国家科学基金会;

关键词：

FrFT; Weighted Variance; Threshold Filtering; SNR;

D O I：

10.1109/EECS.2018.00030

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The Fractional Fourier Transform (FrFT) is applied to the denoising of noisy speech. The optimal transform order of FrFT for single phoneme is determined by using weighted variance method. Then the soft-hard threshold compromise denoising algorithm is put forward. This method removes the amplitude of noise from noisy phoneme signals in FrFT-domain. Signals are reconstructed by inverse FrFT to get original speech. The experimental results show that this method can effectively remove noise from signals and get a good auditory effect, and this algorithm is of low computational complexity.

引用

页码：118 / 122

页数：5

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