Combination of Beam Forming and Kalman Filter Techniques for Speech Enhancement
In all speech communication settings the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. Kalman filter is an adaptive least square error filter that provides an efficient computational recursive solution for estimating a signal in presence of noises. Beamforming is another possible method of speech enhancement, because, the beamformer minimizes the output signal power but maintains signals from the desired direction. Hence, an optimized cascaded scheme is implemented using the advantages of Kalman filter and Beamforming where the Kalman filter technique followed by Beamforming reduces stationary as well as residual noise. The proposed hybrid method gives better SNR and PESQ values as compared to that of individual techniques, thereby improving the quality of the speech.