Eigen-value Combination Approach for Speech Enhancement

Authors

Huijuan Lu, 1. College of Information Engineering, China Jiliang University, Hangzhou 310018, China;;
Yaqing Liu, 1. College of Information Engineering, China Jiliang University, Hangzhou 310018, China;;
Yanqiu Liu, 1. College of Information Engineering, China Jiliang University, Hangzhou 310018, China;;
Guan Wei, 2. College of Moder Science and Technology, China Jiliang University, Hangzhou 310018, China;

Abstract

Abstract: In order to further suppress noise, a kind of speech enhancement algorithm based on Eigen-value merge was proposed. Eigen-values combination was used to improve the speech quality on the basis of the classic embedded pre-whitening subspace methods. The study shows that, after decomposing the covariance matrix of speech signals with noise, the larger Eigen-value component mainly includes speech information, and the smaller Eigen-value component mainly contains noise. Sorted by Eigen-values from small to big, the adjacent large Eigen-value component replaces with small Eigen-value component, which can effectively suppress noise and improve the quality of speech. Compared with other speech enhancement algorithm, this algorithm based on Eigen value merger can work effectively in a variety of noisy environment, significantly improves the SNR, and has better speech intelligibility.

Recommended Citation

Lu, Huijuan; Liu, Yaqing; Liu, Yanqiu; and Wei, Guan (2020) "Eigen-value Combination Approach for Speech Enhancement," Journal of System Simulation: Vol. 28: Iss. 7, Article 19.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss7/19

First Page

1622

Revised Date

2015-02-01

DOI Link

https://doi.org/

Last Page

1627

CLC

TN912.3

Recommended Citation

Lu Huijuan, Liu Yaqing, Liu Yanqiu, Guan Wei. Eigen-value Combination Approach for Speech Enhancement[J]. Journal of System Simulation, 2016, 28(7): 1622-1627.