DocumentCode :
3587919
Title :
Noise power spectral density matrix estimation based on modified IMCRA
Author :
Qipeng Gong ; Champagne, Benoit ; Kabal, Peter
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
fYear :
2014
Firstpage :
1389
Lastpage :
1395
Abstract :
In this paper, we present a new method for noise power spectral density (PSD) matrix estimation based on IMCRA which consists of two parts. For the auto-PSD (diagonal) estimation, we propose a modification to IMCRA where a special level detector is employed to improve the tracking of non-stationary noise backgrounds. For the cross-PSD (offdiagonal) estimation, we propose to calculate a smoothed cross-periodogram by using estimated noise components derived as residuals after the application of a speech enhancement algorithm on the individual microphone signals. Simulation results show the effectiveness of our proposed approach in estimating the noise PSD matrix and its robustness against reverberation when used in combination with an MVDR-based speech enhancement system.
Keywords :
matrix algebra; microphone arrays; speech enhancement; MVDR-based speech enhancement system; PSD matrix estimation; auto-PSD estimation; cross-PSD estimation; estimated noise components; microphone signals; modified IMCRA; noise power spectral density matrix estimation; nonstationary noise background tracking; smoothed cross-periodogram; special level detector; speech enhancement algorithm; Estimation; Microphones; Noise; Noise measurement; Smoothing methods; Speech; Speech enhancement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
Type :
conf
DOI :
10.1109/ACSSC.2014.7094689
Filename :
7094689
Link To Document :
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