A Speech Enhancement Algorithm Based on Bark-Scale Wavelet Package

Author

Teng, Jian-Fu ; Dong, Jian ; Wang, Shu-Yan ; Bao, Hu ; Wang, Ming-Guo

Author_Institution

Tianjin Univ. of Commerce, Tianjin

Volume

6

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3386

Lastpage

3389

Abstract

The selection of threshold and curse is a key issue to determine the de-noisy effect and distortion of the output signal in speech enhancement algorithm. In this paper, combined with Bark-scale Wavelet Package, the S curve of QNN (Quantum Neural Networks) is introduced to wavelet threshold method to achieve speech enhancement. The simulation result indicates that the method presented is superior to that of traditional soft or hard threshold method. The algorithm presented can improve the quality of voice.

Keywords

distortion; neural nets; signal denoising; speech enhancement; wavelet transforms; bark-scale wavelet package; quantum neural networks; signal denoising; signal distortion; speech enhancement; wavelet threshold; Frequency; Machine learning; Machine learning algorithms; Packaging machines; Signal processing; Signal processing algorithms; Speech enhancement; Wavelet analysis; Wavelet domain; Wavelet transforms; QNN; Speech enhancement; Wavelet package;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370733

Filename

4370733