DocumentCode :
495349
Title :
The Noise Autocorrelation Estimation Based on Optimal Smoothing Recursion and Minimum Energy Algorithm
Author :
Tong, Niu ; Lian-hai, Zhang ; Dan, Qu
Author_Institution :
Zhengzhou Inf. Sci. & Technol. Inst., Zhengzhou, China
Volume :
6
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
465
Lastpage :
468
Abstract :
A noise autocorrelation estimator based on the optimal first-order smoothing recursion and minimum energy algorithm is described in this paper. The estimator can be combined with any speech enhancement algorithm based on subspace which requires an accurate estimate of noise autocorrelation. Unlike the other approaches used to estimation noise autocorrelation, the proposed approach estimated it from the autocorrelation of noisy speech directly. The simulation results show that the proposed estimator performed better than the traditional estimators, especially in the nonstationary noise environment.
Keywords :
speech enhancement; minimum energy algorithm; noise autocorrelation estimation; optimal first-order smoothing recursion; speech enhancement algorithm; Autocorrelation; Computer science; Detectors; Information science; Power engineering and energy; Recursive estimation; Smoothing methods; Speech analysis; Speech enhancement; Working environment noise; Speech enhancement; noise autocorrelation estimation; subspace approach;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.89
Filename :
5170742
Link To Document :
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