Considering non-stationarity for blind signal separation

Author

Ahmed, Alijah ; Rayner, Peter J W ; Godsill, Simon J.

Author_Institution

Dept. of Eng., Cambridge Univ., UK

fYear

1999

fDate

1999

Firstpage

111

Lastpage

114

Abstract

We investigate the exploitation of non-stationarity for signal separation. A second-order decorrelation method is used to separate synthetic independent autoregressive signals that are made up of stationary blocks that have been convolutively mixed. We compare results obtained by not taking into account the non-stationarity with those that do. Under certain conditions, exploiting non-stationarity results in more robust separation. We present simulation results that vindicate this fact. In addition, we apply the decorrelation method to real microphone signals, to see how exploiting non-stationarity affects separation quality

Keywords

array signal processing; autoregressive processes; convolution; decorrelation; microphones; speech processing; blind signal separation; real microphone signals; robust separation; second-order decorrelation method; sensor signal processing; separation quality; signal nonstationarity; simulation results; speech signals; stationary blocks; synthetic independent autoregressive signals; Blind source separation; Cost function; Decorrelation; Finite impulse response filter; Higher order statistics; Independent component analysis; Maximum likelihood estimation; Microphones; Robustness; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Applications of Signal Processing to Audio and Acoustics, 1999 IEEE Workshop on

Conference_Location

New Paltz, NY

Print_ISBN

0-7803-5612-8

Type

conf

DOI

10.1109/ASPAA.1999.810862

Filename

810862