An optimum MMSE post-filter for Adaptive Noise Cancellation in automobile environment

Adaptive Noise Cancellation (ANC) is an effective dual-channel technique for background noise reduction. Due to the presence of uncorrelated noise components at the two inputs in vehicular environments, ANC does not provide sufficient background noise reduction. To alleviate this problem, a complementary linear filter is added to ANC structure. Filter coefficients are determined to make the enhanced signal an MMSE estimation of speech signal. Therefore, the ANC structure is modified to a dual-channel Wiener structure. We prove that this structure is identical to the LMS type ANC which is followed by a Wiener post-filter. A new method is proposed for the noise spectrum estimation in the Wiener post-filter. This method does not require Voice Activity Detectors (VADs) and performs better speech enhancement in nonstationary noisy environments. Experimental results show that the proposed system can overcome the problem efficiently, at the cost of more complexity and more speech distortion.