Kalman filter for speech enhancement in cocktail party scenarios using a codebook-based approach

Enhancement of speech in non-stationary background noise is a challenging task, and conventional single channel speech enhancement algorithms have not been able to improve the speech intelligibility in such scenarios. The work proposed in this paper investigates a single channel Kalman filter based speech enhancement algorithm, whose parameters are estimated using a codebook based approach. The results indicate that the enhancement algorithm is able to improve the speech intelligibility and quality according to objective measures. Moreover, we investigate the effects of utilizing a speaker specific trained codebook over a generic speech codebook in relation to the performance of the speech enhancement system.