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Close Sound Source Localization incorporating Semi-Supervised Variational Bayesian NMF

机译:结合半监督变分贝叶斯NMF的封闭声源定位

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This paper proposes a method to integrate a sound source separation method based on Nonnegative Matrix Factorization approach that is able to cope with partially known acoustic characteristics, and a sound source localization method with a frequency bin selection utilizing the separated signals. The proposed method is effective in the case when the target sound source locates close to a noise source, and the noise characteristics are available owing to the sound sound separation suppress the effect of noise. Numerical simulations showed that the proposed system succeeded to localize two sources of 5° interval, which validates the approach.
机译:本文提出了一种方法,该方法将基于非负矩阵分解方法的声源分离方法与能够解决部分已知的声学特性的方法相结合,并将一种声源定位方法与利用分离的信号进行频点选择相结合。所提出的方法在目标声源靠近噪声源且由于声波分离抑制噪声影响而可获得噪声特性的情况下是有效的。数值模拟表明,所提出的系统成功地定位了两个5°间隔的震源,从而验证了该方法的有效性。

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