Speech enhancement using nonlinear microphone array under nonstationary noise conditions

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. 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 delay-and-sum array, it is shown that: (1) the proposed array performs more than 20% better in word recognition rates under the conditions that the white Gaussian noise is used, (2) the proposed array improves the word recognition rate by about 5% when the interfering noise is a single speaker or the overlap of some speakers, (3) the proposed array improves the word recognition rate by more than 10% when the noise is a nonstationary bubble noise.