Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi 441-8580, Japan.
J Acoust Soc Am. 2009 Dec;126(6):3084-94. doi: 10.1121/1.3257548.
A method which automatically provides the position and orientation of a directional acoustic source in an enclosed environment is proposed. In this method, different combinations of the estimated parameters from the received signals and the microphone positions of each array are used as inputs to the artificial neural network (ANN). The estimated parameters are composed of time delay estimates (TDEs), source position estimates, distance estimates, and energy features. The outputs of the ANN are the source orientation (one out of four possible orientations shifted by 90 degrees and either the best array which is defined as the nearest to the source) or the source position in two dimensional/three dimensional (2D/3D) space. This paper studies the position and orientation estimation performances of the ANN for different input/output combinations (and different numbers of hidden units). The best combination of parameters (TDEs and microphone positions) yields 21.8% reduction in the average position error compared to the following baselines and a correct orientation ratio greater than 99%. Position localization baselines consist of a time delay of arrival based method with an average position error of 34.1 cm and the steered response power with phase transform method with an average position error of 29.8 cm in 3D space.
提出了一种自动提供封闭环境中指向性声源位置和方向的方法。在该方法中，将接收到的信号的估计参数与每个阵列的麦克风位置的不同组合用作人工神经网络 (ANN) 的输入。估计参数由时延估计 (TDE)、源位置估计、距离估计和能量特征组成。ANN 的输出是源方向（四个可能方向之一，每个方向偏移 90 度，或者定义为最接近源的最佳阵列）或二维/三维 (2D/3D) 空间中的源位置。本文研究了不同输入/输出组合（和不同数量的隐藏单元）下 ANN 的位置和方向估计性能。最佳参数组合（TDE 和麦克风位置）与以下基准相比，平均位置误差降低了 21.8%，正确方向比大于 99%。位置定位基准包括基于到达时间延迟的方法，其在 3D 空间中的平均位置误差为 34.1cm，以及基于相变换的导向响应功率方法，其平均位置误差为 29.8cm。
