Speech Enhancement Using Nonlinear Microphone Array Based on Complementary Beamforming

This paper describes a spatial spectral subtraction method by using the complementary beamforming microphone array to enhance noisy speech signals for speech recognition. The complementary beamforming is based on two types of beamformers designed to obtain complementary directivity patterns with respect to each other. In this paper, it is shown that the nonlinear subtraction processing with complementary beamforming can result in a kind of the spectral subtraction without the need for speech pause detection. In addition, the optimization algorithm for the directivity pattern is also described. To evaluate the effectiveness, speech enhancement experiments and speech recognition experiments are performed based on computer simulations under both stationary and nonstationary noise conditions. In comparison with the optimized conventional delayand-sum (DS) array, it is shown that: (1) the proposed array improves the signal-to-noise ratio (SNR) of degraded speech by about 2 dB and performs more than 20% better in word recognition rates under the conditions that the white Gaussian noise with the input SNR of −5 or −10 dB is used, (2) the proposed array performs more than 5% better in word recognition rates under the nonstationary noise conditions. Also, it is shown that these improvements of the proposed array are same as or superior to those of the conventional spectral subtraction method cascaded with the DS array. key words: speech enhancement, microphone array, complementary beamforming, spectral subtraction, speech recognition