To enhance the noisy speech signal, a perceptual weighting based Kalman filtering is investigated. Our study is to seek a high perceptual quality of speech enhancement system which optimizes the trade-off between the speech distortion and noise reduction. Using perceptual weighting to replace the masking threshold avoids the frequency domain complexity, it is suitable for time domain Kalman filtering to estimate the state-space vector in only the time domain. Through many simulations, it is demonstrated that the proposed perceptual Kalman filtering outperforms the conventional Kalman filtering
['Chang Huai You', 'Susanto Rahardja', 'Soo Ngee Koh']
Perceptual Kalman Filtering Speech Enhancement