Binary microphone microarray voice beam forming method

Abstract

The invention discloses a binary microphone microarray voice beam forming method, which comprises the following steps of: constructing a microphone microarray so as to receive external signals; analyzing the signals to obtain relative time delay of a target sound source relative to two microphones; respectively carrying out time delay correction on digital signals corresponding to the two microphones according to the time delay to obtain corrected signals; completing fixed beam forming according to the two corrected signals; obtaining a noise reference signal by using a block matrix according to the two corrected signals; by using a frequency domain self-adaption processing algorithm, converting the fixed beam forming into a primary gain signal and converting the noise reference signal into an estimated noise reference signal; and removing noise energy out of the primary gain signal to obtain a final beam forming signal. The invention has the advantages of good generality, low dependence on hardware, no requirement on angles of the target sound source and a noise source, application to a moving environment, a mixed-sound environment and a nonstationary noise environment and good denoising effect.

Description

technical field [0001] The invention relates to the technical field of voice enhancement, in particular, the invention relates to a microphone microarray target voice beamforming method for the mobile phone field. Background technique [0002] At present, mobile phones have become an essential communication device in our daily life, so the quality of calls has become an issue of increasing concern, especially in a noisy environment, which will seriously affect the communication between the two parties. In order to solve this problem, voice noise reduction Technology came into being. [0003] In order to suppress noise, a single-channel noise reduction method and a microphone array beamforming noise suppression method have emerged. For single-channel noise, techniques such as spectral subtraction and Wiener filtering are commonly used. The disadvantages of these methods are that the suppression effect on non-stationary noise is poor, and it will cause large speech distortion...

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the disadvantages of poor versatility, strong dependence on hardware, strict requirements on target sound source and noise source angle, high algorithm complexity and small application range in the prior art, the present invention provides a It has low dependence and does not require strict angle constraints between the target sound source and the noise source. It is suitable for mobile environments, reverberation environments and non-stationary noise environments, and has a good denoising effect. Binary microphone microarray speech beamforming method

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