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A Novel Multiple Sparse Source Localization Using Triangular Pyramid Microphone Array

机译:使用三角金字塔麦克风阵列的新型多稀疏源定位

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Making use of the time-frequency spectra sparsity of the speech sources and the spatial and inter-relation information provided from a triangular pyramid microphone array (TPMA), the ratio of the inter-sensor phase difference (RIPD) is defined and a direct relationship between RIPD information and the direction of arrival (DOA) of each source is obtained. A novel multiple speech source localization algorithm (named as TPMA-RIPD) using the histogram clustering technique is proposed, which has been evaluated by several simulation experiments. Experimental results show that the TPMA-RIPD algorithm is able to provide high source localization accuracy in noisy environment for all angles. It is also able to estimate multiple speech sources when the number of sources is larger than that of the microphones used.
机译:利用语音源的时间频谱稀疏性以及三角金字塔麦克风阵列(TPMA)提供的空间和相互关系信息,定义了传感器间相位差的比率(RIPD)并具有直接关系获得RIPD信息和每个源的到达方向(DOA)之间的差值。提出了一种利用直方图聚类技术的新型多语音源定位算法(称为TPMA-RIPD),并通过多次仿真实验对其进行了评估。实验结果表明,TPMA-RIPD算法能够在嘈杂的环境中为所有角度提供较高的源定位精度。当语音源的数量大于所使用麦克风的数量时,它还可以估计多个语音源。

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