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Localization of Multiple Simultaneously Active Speakers in an Acoustic Sensor Network

机译:多个同时有源扬声器在声传感器网络中的定位

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This paper addresses the localization of an unknown number of acoustic sources in an enclosure. We extend a well established algorithm for localization of acoustic sources, which is based on the Expectation Maximization (EM) algorithm for clustering of phase differences by a Gaussian mixture model. Supporting a more appropriate probabilistic model for spherical data such as direction of arrival or phase differences, the von Mises distribution is used to derive a localization algorithm for multiple simultaneously active sources. Experiments with simulated room impulse responses confirm the superiority of the proposed algorithm to the existing method in terms of localization performance.
机译:本文介绍了机箱中未知数量声源的定位。我们扩展了一种完善的声源定位算法,该算法基于期望最大化(EM)算法,用于通过高斯混合模型对相差进行聚类。 von Mises分布支持球形数据(如到达方向或相位差)的更合适的概率模型,可用于导出多个同时活动源的定位算法。模拟房间脉冲响应的实验证实了该算法在定位性能方面优于现有方法。

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