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On the Impact of Quantization on Binaural MVDR Beamforming

机译:量化对双声道MVDR波束成形的影响

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Multi-microphone noise reduction algorithms in binaural hearing aids which cooperate through a wireless link have the potential to become of great importance in future hearing aid systems. However, limited transmission capacity of such devices necessitates the data compression of signals transmitted from one hearing aid to the contralateral one. In this paper we study the impact of quantization as a data compression scheme on the performance of the multi-microphone noise reduction algorithms. Using the binaural minimum variance distortionless response (BMVDR) beamformer as an illustration, we propose a quantization aware beamforming scheme which uses a modified cross power spectral density (CPSD) of the system noise including the quantization noise (QN). Moreover, several assumptions on the QN are investigated in the proposed method. Based on the output SNR, we compare different variations of the proposed method with the conventional BMVDR beamformer. The results confirm the improved performance of the proposed method.
机译:通过无线链路协作的双耳助听器中的多麦克风降噪算法可能在未来的助听器系统中变得非常重要。然而,这种设备的有限的传输容量使得必须对从一种助听器传输到对侧的助听器的信号进行数据压缩。在本文中,我们研究了作为数据压缩方案的量化对多麦克风降噪算法性能的影响。使用双耳最小方差无失真响应(BMVDR)波束形成器作为说明,我们提出了一种量化感知波束形成方案,该方案使用系统噪声(包括量化噪声(QN))的经过修改的交叉功率谱密度(CPSD)。此外,在提出的方法中研究了关于QN的几个假设。基于输出信噪比,我们将提出的方法与传统的BMVDR波束形成器进行比较。结果证实了所提出方法的改进性能。

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