Adaptive beamforming for acoustic echo cancellation using measured array models and subband filtering

Abstract

Acoustic echo that can substantially undermine speech quality is one of the key issues must be addressed in practical telecommunication systems. In this paper, an evolutionary exposition is given in regard to the enhancing strategies for acoustic echo cancelers (AEC). On the basis basic adaptive filtering, a highly directional microphone array is designed as a fixed beamformer (FBF) to focus on the near-end speaker and suppress the echo from the far-end as well as noise and interference from the background. Design of the beamformer is based on array models interpolated from measured frequency responses. Subband (SB) filtering with polyphase decomposition is exploited to accelerate the cancellation process with multiple choice of step size in the subbands. To further enhance the canceler, adaptive generalized sidelobe canceler (GSC) can be utilized, which is comprised of a FBF for the near-end speech and an adaptive blocking module for the echo and noise. Objective tests in terms of echo return loss enhancement (ERLE) and perceptual evaluation of speech quality (PESQ) are conducted to compare four algorithms with various combinations of enhancement. The results show that the GSC-SB-AEC approach has attained the highest ERLE and best speech quality, even in a double-talk scenario.