Poster: Robust Neuro-Fuzzy Speaker Localization Using a Circular Microphone Array
Poster: Robust Neuro-Fuzzy Speaker Localization Using a Circular Microphone Array
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海报：使用圆形麦克风阵列进行鲁棒神经模糊扬声器定位
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
G. Fink
中科院分区：
文献类型：
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作者：
A. Plinge;Marius H. Hennecke;G. Fink
麦克风阵列处理的一个主要应用领域是声源定位，主要是说话人的声源定位。与大多数基于相关测量的最先进的方法相反，我们提出了一个神经启发系统，该系统将有关人类空间听力的发现推广到多通道情况。它模仿了人类耳蜗和听觉中脑的处理过程。为了提高定位质量，提出了一种新的峰值生成方法，称为峰值超过平均位置（PoAP）。使用模糊组合来去除假定的伪影。与人类听众相比，我们采用多个传感器来获得混响和嘈杂环境中的鲁棒性。后处理估计并发说话者的位置。通过与已知的转向响应功率方法的比较，证明了所提系统的鲁棒性。最后，我们用真实混响录音证明了我们的实时神经模糊模型在并发说话人定位任务中的适用性。
A major application area of microphone array processing is the localization of sound sources, mainly of speaking persons. In contrast to most state-of-the-art approaches that are based on correlation measures, we propose a neurologically inspired system that generalizes findings about human spatial hearing to the multi-channel case. It mimics the processing in the human cochlea and the auditory mid-brain. To enhance the localization quality, a new spike generation approach is introduced, termed peak-over-average position (PoAP). A fuzzy combination is used to remove putative artifacts. In contrast to a human listener we employ multiple sensors to gain robustness in reverberant and noisy environments. Post-processing estimates the locations of concurrent speakers. The robustness of the proposed system is shown by comparison with the wellknown steered response power approach. Finally, we show the applicability of our realtime neuro-fuzzy model to the concurrent speaker localization task using real reverberant recordings.