Abstract
This work studies a wind noise reduction approach for communication applications in a car environment. An endfire array consisting of two microphones is considered as a substitute for an ordinary cardioid microphone capsule of the same size. Using the decomposition of the multichannel Wiener filter (MWF), a suitable beamformer and a single-channel post filter are derived. Due to the known array geometry and the location of the speech source, assumptions about the signal properties can be made to simplify the MWF beamformer and to estimate the speech and noise power spectral densities required for the post filter. Even for closely spaced microphones, the different signal properties at the microphones can be exploited to achieve a significant reduction of wind noise. The proposed beamformer approach results in an improved speech signal regarding the signal-to-noise-ratio and keeps the linear speech distortion low. The derived post filter shows equal performance compared to known approaches but reduces the effort for noise estimation.
Highlights
Hands-free communication applications in a car environment always face the problem of unwanted noise components in the microphone signals
From these assumptions follows for closely spaced microphones that a simple delay-and-sum (DS) beamformer achieves maximum signal-to-noise-ratio (SNR) beamforming, because equal Acoustic transfer function (ATF) from the speech source to the microphones can be assumed for low frequencies
We propose a wind noise reduction approach for a closely spaced microphone array consisting of two micro-electro-mechanical system (MEMS) microphones, which is considered as a substitute for an ordinary cardioid microphone capsule
Summary
Hands-free communication applications in a car environment always face the problem of unwanted noise components in the microphone signals. The approach is based on the assumption that the wind noise is uncorrelated at the microphones, while having equal noise power spectral densities, but arbitrary acoustic transfer functions (ATFs) From these assumptions follows for closely spaced microphones that a simple delay-and-sum (DS) beamformer achieves maximum signal-to-noise-ratio (SNR) beamforming, because equal ATFs from the speech source to the microphones can be assumed for low frequencies. The proposed wind noise reduction approach is derived from the commonly used speech distortion weighted multichannel Wiener filter [3], which is defined as GMWF = (RS + μRN)−1. Where L denotes the block length of the short-time Fourier transform After this alignment, we assume that the ATFs in H are identical, because the low frequency speech components have a large wavelength compared with the microphone distance.
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