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Real-Time Multiple Sound Source Localization and Counting Using a Circular Microphone Array

机译:使用圆形麦克风阵列进行实时多声源定位和计数

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In this work, a multiple sound source localization and counting method is presented, that imposes relaxed sparsity constraints on the source signals. A uniform circular microphone array is used to overcome the ambiguities of linear arrays, however the underlying concepts (sparse component analysis and matching pursuit-based operation on the histogram of estimates) are applicable to any microphone array topology. Our method is based on detecting time-frequency (TF) zones where one source is dominant over the others. Using appropriately selected TF components in these “single-source” zones, the proposed method jointly estimates the number of active sources and their corresponding directions of arrival (DOAs) by applying a matching pursuit-based approach to the histogram of DOA estimates. The method is shown to have excellent performance for DOA estimation and source counting, and to be highly suitable for real-time applications due to its low complexity. Through simulations (in various signal-to-noise ratio conditions and reverberant environments) and real environment experiments, we indicate that our method outperforms other state-of-the-art DOA and source counting methods in terms of accuracy, while being significantly more efficient in terms of computational complexity.
机译:在这项工作中,提出了一种多声源定位和计数方法,该方法对源信号施加了稀疏的稀疏性约束。统一的圆形麦克风阵列用于克服线性阵列的歧义,但是基本概念(稀疏分量分析和估计直方图上基于匹配追踪的运算)适用于任何麦克风阵列拓扑。我们的方法基于检测时频(TF)区域,其中一个来源占主导地位。通过在这些“单源”区域中使用适当选择的TF分量,通过将匹配的基于跟踪的方法应用于DOA估计的直方图,所提出的方法可以联合估计活动源的数量及其相应的到达方向(DOA)。该方法具有出色的DOA估计和源计数性能,并且由于其复杂性低而非常适合于实时应用。通过仿真(在各种信噪比条件和混响环境中)和真实环境实验,我们表明我们的方法在准确性方面优于其他最新的DOA和源计数方法,同时效率显着提高在计算复杂度方面。

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