Robust Adaptive Noise Canceller Algorithm with Snr-Based Stepsize Control and Noise-Path Gain Compensation

Abstract

This paper proposes a robust adaptive noise canceller algorithm with SNR-based stepsize control and noise-path gain compensation. The stepsize for coefficient adaptation is controlled with an estimated SNR for low distortion of the output signal and a small residual noise. A second SNR estimate, which is the output over an adjusted reference input, initially controls the stepsize to promote co-efficient growth, followed by a more accurate first SNR estimate defined as the output over the noise replica. The power gap between the reference input and the noise replica is compensated for by a factor estimated during an initial target-signal absence. Switchover from the second to the first SNR estimate takes place when the coefficient growth is saturated to guarantee robustness to different noise-path gains. Evaluations with clean speech and noise recorded at a busy station demonstrate that conventional algorithms exhibit initial in-crease in the coefficient error and never reach the switchover status at a high SNR whereas the proposed algorithm achieves as much as 8dB smaller coefficient error than that without gain compensation.