A fast adaptive kalman filtering algorithm for speech enhancement under stationary noise environment

Abstract

Kalman Filtering is one of the time domain speech-enhancement techniques. The conventional Kalman filtering technique involves more number of matrix operations. The complexity of matrix operations is reduced by fast adaptive Kalman Filtering technique. The proposed method of fast adaptive filtering technique is simple and gives best results for stationary noises. From the simulation results, it is seen that the proposed method of Kalman filtering is more effective in obtaining the clean speech signal. The performance of this filter is compared with the conventional method with respect to the signal to noise ratio and the execution time.