基于赋值问题的频域卷积源分离中排列模糊度求解方法

H. N. Vuong, Quoc Nguyen, H. L. Tran
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引用次数: 0

摘要

本文提出了一种有效的卷积混合信号频域盲源分离方法。频率方法的主要困难是排列问题。在该方法中,我们使用分配问题(AP)方法来解决频域上的排列歧义。在我们的工作中,我们应用不同的算法来求解AP以找到最优解。此外,通过使用一个简单的检查程序,该算法只能解决几个频率盒中的排列问题,而不是所有的。该方法已被证明比以往使用AP方法的计算效率更高。用语音数据进行了计算机仿真实验,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assignment problem-based approach for solving permutation ambiguity in frequency domain convolutive source separation
In this paper, we propose an effective method for blind source separation of convolutive mixtures in the frequency domain. The main difficulty in a frequency approach is the permutation problem. In the proposed method, we use the Assignment Problem (AP) approach to solve permutation ambiguity in the frequency domain. In our work, we apply different algorithms to solve the AP to find the optimal solution. Furthermore, by using a simple check procedure, the algorithm has to only solve the permutation problem in a few frequency bins instead of all. This method has been proven more efficient on computation than the previous methods using the AP approach. Computer simulation experiments with speech data are presented to illustrate the proposed method.
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