A new method for speech enhancement in colored noise is proposed in this paper. A Kalman filter concatenated with a post-filter based on masking properties of human auditory systems is proposed for the problem. A recursive approach to compute the noise covariance matrix is used for estimating the colored noise statistics. In the post-filter, both time domain masking properties and frequency domain masking properties are taken into account. From the calculated masking level, the noisy speech spectrum is adjusted accordingly. Simulation results show that the proposed approach has the best performance compared with other recent methods, evaluated with PESQ scores.

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Conference Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing
Citation
Ma, N. (Ning), Bouchard, M. (Martin), & Goubran, R. (2004). Perceptual Kalman filtering for speech enhancement in colored noise. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings.