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Foreground suppression for capturing and reproduction of crowded acoustic environments

机译:前景抑制可捕获和再现拥挤的声学环境

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Traditionally, sensor arrays and spatial filtering aim to enhance individual sources by suppressing ambient noise and reverberation. In this paper, the exactly opposite problem is examined, that of suppressing individual sources in favour of the ambient sound and of the whole acoustic scene in general. We consider a compact circular sensor array which is embedded in a crowded ambient acoustic environment and is at the same time prone to interference from directional speech originating from multiple nearby speakers. We propose a method for suppressing the undesired components and we compare its performance with two established approaches in spatial audio processing, namely, direct-to-diffuse decomposition and Primary-Ambient Extraction (PAE). Experimental results and a listening test which are presented illustrate the superiority of our method.
机译:传统上,传感器阵列和空间滤波旨在通过抑制环境噪声和混响来增强单个信号源。在本文中,研究了完全相反的问题,即抑制单个信号源,而偏向于环境声音和整个声音场景。我们考虑一个紧凑的圆形传感器阵列,该阵列嵌入在拥挤的环境声环境中,同时容易受到来自附近多个扬声器的定向语音的干扰。我们提出了一种抑制不希望有的分量的方法,并将其性能与两种在空间音频处理中已建立的方法进行了比较,即直接扩散分解和主环境提取(PAE)。实验结果和听力测试表明了我们方法的优越性。

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