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Performance analysis of filter bank based M-estimators for interference suppression in speech signals

This paper presents a Filter bank based M-estimator technique for analyzing the signals corrupted with interference and noise. The interference is detected from the frequency spectra of the subband signals at the output of the Analysis filter bank. A new M-estimator based iterative technique is proposed to eliminate the detected interference. The Cosine modulated filter bank is used in designing analysis and synthesis filters because of its Perfect reconstruction and easy implementation property. The efficacy of the proposed technique is demonstrated through simulation results considering a speech signal with added interference. Further, the performance of M-estimator based technique is compared with the band elimination technique for interference cancellation in speech signals. Simulation results show the effectiveness of the proposed technique in the analysis of noise contaminated speech signals.