A new adaptive algorithm for stereophonic acoustic echo canceller

Stereophonic sound becomes more important in a growing number of hands-free applications where spatial realism is demanded. Such hands-free systems need stereophonic acoustic echo cancellers to reduce echoes that result from coupling between loudspeakers and microphones. In this paper, we propose a new adaptive algorithm for an stereophonic acoustic echo canceller based on human auditory properties and affine projection (AP) algorithm. The proposed algorithm employs a pre-processor generating speech-like noise to decorrelate the input signals without degrading perceptual speech quality. The decorrelation is based on the masking patterns of the human auditory system. By showing that the AP algorithm can be represented by a vector update as a combination of the Gram-Schmidt (GS) orthogonalization followed by the normalized LMS (NLMS) algorithm, the proposed adaptive algorithm integrates the pre-processor into the adaptive algorithm. Subjective listening test and computer simulation show the effectiveness of the proposed algorithm