Neural network-based microphone array learning of temporal-spatial patterns of input signals

Akihiro Iseki, K. Ozawa, Yuichiro Kinoshita
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引用次数: 6

Abstract

A sharp directional microphone array system was previously developed using a neural network. However, the system cannot distinguish two signals with different frequencies because it learns only the spatial pattern of the sound pressure distribution of the input signals. To overcome this problem, herein we propose a system that learns the temporal-spatial pattern of the input signals. The proposed system successfully obtains a wide-band super-directivity.
基于神经网络的麦克风阵列输入信号时空模式学习
利用神经网络技术开发了一种尖锐定向麦克风阵列系统。然而,系统无法区分两个不同频率的信号,因为它只学习输入信号的声压分布的空间模式。为了克服这个问题,我们提出了一个学习输入信号的时空模式的系统。该系统成功地获得了宽带超指向性。
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