Towards robust close-talking microphone arrays for noise reduction in mobile phones.

Adaptive close-talking differential microphone arrays (ACT-MAs) inherently suppress farfield noise while emphasizing desired nearfield signals. This paper discusses the applicability of ACT-MAs for noise reduction in mobile phones. In order to utilize the advantages of ACTMAs, we need to improve the robustness to microphone mismatch and improve parameter estimation accuracy. In this paper we propose a method to improve the robustness of the ACTMA algorithm by taking microphone gain mismatch into account in the detection of background noise and mobile phone user activity, performing online microphone gain calibration, steering the null of the ACTMA to the rear of the mobile phone, and performing parameter estimation only when mobile phone user activity is detected. Thus, the robust ACTMA is applicable for performing noise reduction in mobile phones. Experiments with recorded data demonstrate the effectiveness of this method.