A new cross correlation based double talk detection algorithm for nonlinear acoustic echo cancellation

Acoustic echo canceller (AEC) is present in mobile communication system which is a popular mode of personal communication systems. AECs are used to eliminate the echo which dampens the speech signal and reduces the efficiency of signal transmission. The major problems faced by AECs are non-linearity and double talk. Non-linearity occurs due to the use of low cost electronic loud speaker, microphones and poorly designed enclosures in an AEC framework. Non-linearity causes vibration and harmonic distortion and also degrades the speech quality. Double talk occurs when both near end and far end speakers are active at a time. A Double Talk Detector (DTD) senses the presence of the two remote end speakers and modifies the weights of the filter through an adaptive algorithm to prevent the divergence of the adaptive filter. Double talk detection algorithms like Geigel, cross correlation and optimized cross correlation DTD are used to improve the performance of AECs. In this paper a unique way is proposed for the use of cross correlation between the far end signal and the received signal to obtain an efficient algorithm for double talk detection. Variable Step Size Least Mean Square algorithm is used as the adaptive algorithm in the proposed method.