Speech Signal Enhancement Using Neural Network and Wavelet Transform

被引：0

作者：

Daqrouq, Khaled ^{[1
]}

Abu-Isbeih, Ibrahim N. ^{[1
]}

Alfauori, Mikhled ^{[1
]}

机构：

[1] Philadelphia Univ, Dept Commun & Elect Engn, Amman 19392, Jordan

来源：

2009 6TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS AND DEVICES, VOLS 1 AND 2 | 2009年

关键词：

Speech signal; Neural network; Discrete wavelet transform; NOISE;

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：

Speech enhancement is concerned with the processing of corrupted or noisy speech signal in order to improve the quality or intelligibility of the signal. Our goal is to enhance speech signal corrupted by noise to obtain a clean signal with higher quality. However, the presence of noise in speech signals will contribute to a high degree of inaccuracy in a system that requires speech processing. This idea of noise cancellation for the speech signal was processed through the neural networks. Three methods were tested: 1. The adaptive linear neuron (ADALINE). 2. Feed Forward Neural Network Enhancement Method FFNN 3. Wavelet Transform and Adaline Enhancement Method. The results obtained showed high quality due to fast processing and high signal-noise-ratio. The tested signal was enhanced 10 dB by Adaline, 3 dB by FFNN and 8 dB by Wavelet Transform and Adaline Enhancement Method.

引用

页码：826 / 831

页数：6

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