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An Adaptive Non-Linear Process for Under-Determined Virtual Microphone Beamforming

机译:用于欠确定虚拟麦克风波束形成的自适应非线性过程

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Virtual microphone beamforming techniques are attractive for devices limited by space constraints. These techniques synthesize virtual microphone signals via interpolation algorithms. We propose to extend existing virtual microphone signal interpolation by employing an adaptive non-linear (ANL) process for acoustic beamforming. The proposed ANL based interpolation utilizes a target-presence probability criteria to determine the degree of non-linearity. The beamformer output is then derived using a combination between interpolations during target inactive zones and target active zones. Such combination offers a trade-off between reducing interference and target signal distortion. We apply the proposed ANL-based interpolator to the maximum signal-to-noise ratio (MSNR) beamformer and compare its performance against conventional beamforming and virtual microphone based beamforming methods in under-determined situations.
机译:虚拟麦克风波束形成技术对于受空间限制限制的设备具有吸引力。 这些技术通过插值算法合成虚拟麦克风信号。 我们建议通过采用用于声学波束形成的自适应非线性(ANL)过程来扩展现有的虚拟麦克风信号插值。 所提出的基于ANL的插值利用目标存在概率标准来确定非线性度的程度。 然后使用目标非活动区域期间的插值和目标有源区域之间的插值之间的组合导出波束形成器输出。 这种组合在降低干扰和目标信号失真之间提供了折衷。 我们将所提出的基于ANL的内插器应用于最大信噪比(MSNR)波束形成器,并将其性能与在确定的情况下的基于传统波束形成和虚拟麦克风的比较。

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