Acoustic Echo Cancellation Using PEVD Based Adaptive Kalman Filter

Abstract

Abstract:In this paper a PEVD (Polynomial Eigen Value Decomposition) based adaptive kalman filter is proposed for Acoustic Echo Cancellation (AEC) in the presence of noise. Acoustic echo is the phenomenon when the speaker listens to his own voice after some delay while speaking to his fellow mate on a call. The presence of acoustic coupling between the loudspeakers and the near-end microphone signal produces an undesired acoustic echo, which reduces the speech quality. Existing AEC system implemented adaptive kalman filter which results in less output efficiency in the noisy environment. In the proposed method, the near end speech is separated from the acoustic echo as well as from the surrounding noise by using PEVD based adaptive kalman filter. Initially mixed microphone signal is pre-processed by Polynomial Eigen Value Decomposition which strongly de-correlates the signal and also de-correlates out the noise. The pre-processed signal is passed through adaptive kalman filter for estimation of the acoustic echo. The efficiency of the output is calculated using Echo Return Loss Enhancement (ERLE). If the ERLE lies in the range of 30-40 dB indicates the good echo cancellation. The simulations show that the proposed PEVD based adaptive kalman method provides higher cancellation of echo. The simulations are being carried out in Matlab 2016a.

Effectiveness of regulatory technology implementation in Indonesian banking sector to prevent money laundering and terrorist financing

“…The excess Kurtosis value of each indicator is in the range of 0.107#Â# 5.770. A positive excess Kurtosis value (>0) indicates that the data has a high level of sharpness and is classified as leptokurtosis (Kothandaraman and Pachaiyappan, 2013). The Skewness value of each indicator is in the range of À1.111 #Â# À2.333.…”