Title
Multichannel Wiener filter estimation using source location knowledge for speech enhancement
Abstract
In this paper a technique for estimating the single channel Wiener filter post-processor using two complementary adaptive near-field beamformers is presented as an alternative to voice activity detection for speech enhancement applications. Two near-field beamformers, the MVDR beamformer and an adaptive nullformer based on noise to signal maximisation, are used to generate estimates of signal and noise statistics which can be used to compute an estimate of the single channel Wiener filter for noise reduction. It is demonstrated that the performance of the estimated filter compares well with the perfect Wiener filtering case, and shows good improvement in speech intelligibility.
Year
DOI
Venue
2014
10.1109/SSP.2014.6884574
Statistical Signal Processing
Keywords
Field
DocType
Wiener filters,array signal processing,channel estimation,speech enhancement,MVDR beamformer,Wiener filtering,adaptive near-field beamformers,adaptive nullformer,multichannel Wiener filter estimation,near-field beamformers,noise reduction,noise statistics,noise to signal maximisation,single channel Wiener filter post-processor,source location knowledge,speech enhancement,speech intelligibility,voice activity detection,Speech enhancement,Wiener filtering,adaptive filters,beam-forming
Wiener filter,Speech enhancement,Computer science,Wiener deconvolution,Speech recognition
Conference
Citations 
PageRank 
References 
1
0.35
4
Authors
3
Name
Order
Citations
PageRank
CraigA. Anderson120.77
Paul D. Teal210413.58
Mark A. Poletti3132.04