Speech signal enhancement using neural network and wavelet transform

Author

Daqrouq, Khaled ; Abu-Isbeih, Ibrahim N. ; Alfauri, M.

Author_Institution

Dept. of Commun. & Electron. Eng., Philadelphia Univ., Amman

fYear

2009

fDate

23-26 March 2009

Firstpage

1

Lastpage

6

Abstract

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.

Keywords

feedforward neural nets; speech enhancement; speech intelligibility; wavelet transforms; adaptive linear neuron; feed forward neural network enhancement method; neural network; noise cancellation; speech processing; speech signal enhancement; speech signal intelligibility; speech signal quality; wavelet transform; Feedforward neural networks; Feeds; Neural networks; Neurons; Noise cancellation; Signal processing; Speech enhancement; Speech processing; Testing; Wavelet transforms; Discrete wavelet transform; Neural network; Speech signal;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Devices, 2009. SSD '09. 6th International Multi-Conference on

Conference_Location

Djerba

Print_ISBN

978-1-4244-4345-1

Electronic_ISBN

978-1-4244-4346-8

Type

conf

DOI

10.1109/SSD.2009.4956823

Filename

4956823