DocumentCode :
1300843
Title :
A Wiener Filter Approach to Microphone Leakage Reduction in Close-Microphone Applications
Author :
Kokkinis, Elias K. ; Reiss, Joshua D. ; Mourjopoulos, John
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Patras, Patras, Greece
Volume :
20
Issue :
3
fYear :
2012
fDate :
3/1/2012 12:00:00 AM
Firstpage :
767
Lastpage :
779
Abstract :
Microphone leakage is one of the most prevalent problems in audio applications involving multiple instruments and multiple microphones. Currently, sound engineers have limited solutions available to them. In this paper, the applicability of two widely used signal enhancement methods to this problem is discussed, namely blind source separation and noise suppression. By extending previous work, it is shown that the noise suppression framework is a valid choice and can effectively address the problem of microphone leakage. Here, an extended form of the single channel Wiener filter is used which takes into account the individual audio sources to derive a multichannel noise term. A novel power spectral density (PSD) estimation method is also proposed based on the identification of dominant frequency bins by examining the microphone and output signal PSDs. The performance of the method is examined for simulated environments with various source-microphone setups and it is shown that the proposed approach efficiently suppresses leakage.
Keywords :
Wiener filters; microphones; PSD estimation method; Wiener filter approach; audio applications; blind source separation; close-microphone applications; dominant frequency bins; leakage suppression; microphone leakage reduction; multichannel noise; multiple instruments; multiple microphones; noise suppression; power spectral density; signal enhancement methods; simulated environments; single channel Wiener filter; sound engineers; source-microphone setups; Acoustics; Estimation; Instruments; Microphones; Noise; Source separation; Speech processing; Microphone leakage; Wiener filter; multichannel audio enhancement; noise suppression; power spectral density (PSD) estimation; source separation;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2011.2164534
Filename :
5989847
Link To Document :
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