Kalman filter for robust noise suppression in white and colored noises

This paper deals with the problem of noise suppression for white and colored noises. Kalman filter based noise suppression is well known as effective approach, and usually performs the parameter estimation algorithm of AR (auto-regressive) system and then the Kalman filter algorithm. In this paper, we propose Kalman filter for robust noise suppression without the conception of AR system. The algorithm aims to achieve robust noise suppression using only Kalman filter theory from the canonical state space models with (i) a state equation composed of the speech signal and (ii) an observation equation composed of the speech signal and additive noise. We also show the effectiveness of the proposed method, which utilizes Kalman filter theory for the proposed canonical state space model with the colored driving source, using numerical results and subjective evaluation results.