An Adaptive Echo Cancellation Method Based on a Blind Signal Separation

This paper presents a new adaptive echo cancellation (AEC) method base on a blind signal separation (BSS) to reduce the impact of the background noise and echo of the enclosure room on the speech communication signal. The correlation and negentropy of signals are used to distinguish the useful speech signal from several separated signals to solve the problem of the uncertainty of BSS. During single talk, this method separates the echo from noise using the echo mixture as a reference signal to AEC, by which the performance of AEC is improved. During double talk, the near-end speech signal can be accurately separated from the mixture signals by BSS. The experiment results show that our algorithm can raise the output SNR of the canceler by about 10 dB compaired to NLMS algorithm.