首页> 外文会议>International Conference on Spoken Language Processing; 20041004-08; Jeju(KR) >DOA ESTIMATION OF SPEECH SIGNALS USING SEMI-BLIND SOURCE SEPARATION TECHNIQUES
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DOA ESTIMATION OF SPEECH SIGNALS USING SEMI-BLIND SOURCE SEPARATION TECHNIQUES

机译:使用半盲源分离技术对语音信号进行DOA估计

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In this paper we investigate the application of complex independent component analysis (ICA) to the direction of arrival (DOA) estimation problem of wideband signals. The ICA based technique is semi-blind in the sense that the structure of the array is known to be uniform and linear (ULA). We show that when the array is ULA the mixing matrix is forced to have the structure imposed by the directivity vectors of the microphone array. ICA is applied to the spectral bins having the higher SNRs. The DOAs are derived from the histogram and clustering of the angle of arrivals of all high SNR spectral bins. The effectiveness of the approach is evaluated on speech signals and is compared against a variety of wideband DOA estimation techniques based on second order statistics.
机译:在本文中,我们研究了复杂独立分量分析(ICA)在宽带信号到达方向(DOA)估计问题中的应用。基于ICA的技术是半盲的,因为已知阵列的结构是均匀且线性的(ULA)。我们表明,当阵列为ULA时,混合矩阵必须具有麦克风阵列的方向向量所强加的结构。 ICA被应用于具有较高SNR的频谱仓。 DOA从所有高SNR频谱仓的直方图和到达角的聚类中得出。该方法的有效性在语音信号上进行了评估,并与基于二阶统计量的各种宽带DOA估计技术进行了比较。

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