Publications
カンファレンス (国際) Robust Adaptive Noise Canceller Algorithm with SNR-Based Stepsize Control and Noise-Path Gain Compensation
Akihiko Sugiyama
2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2022)
2022.5.8
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 coefficient 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 increase 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.
Paper :
Robust Adaptive Noise Canceller Algorithm with SNR-Based Stepsize Control and Noise-Path Gain Compensation
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