Audio source separation of convolutive mixtures

N. Mitianoudis, M. Davies
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引用次数: 153

Abstract

The problem of separation of audio sources recorded in a real world situation is well established in modern literature. A method to solve this problem is blind source separation (BSS) using independent component analysis (ICA). The recording environment is usually modeled as convolutive. Previous research on ICA of instantaneous mixtures provided solid background for the separation of convolved mixtures. The authors revise current approaches on the subject and propose a fast frequency domain ICA framework, providing a solution for the apparent permutation problem encountered in these methods.
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卷积混合音频源分离
在现代文学中,在现实世界中记录的音源分离问题已经得到了很好的证实。一种解决这一问题的方法是利用独立分量分析(ICA)进行盲源分离。记录环境通常被建模为卷积。以往瞬态混合物ICA的研究为卷积混合物的分离提供了坚实的背景。作者修改了现有的方法,提出了一个快速的频域ICA框架,为这些方法中遇到的明显排列问题提供了解决方案。
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