Under-determined source separation based on power spectral density estimated using cylindrical mode beamforming

Yusuke Hioka, T. Betlehem
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引用次数: 6

Abstract

Sound source signals can be separated using Wiener post-filters calculated by estimating the power spectral densities (PSDs) of sources from the outputs of a set of beamformers. This approach has been shown effective in the under-determined case where the number of sources to be separated exceeds the number of microphones. In this paper, a limit on the maximum number of separable sources is derived beyond which the problem becomes rank deficient. This study reveals the number of sources that can be separated simultaneously is related to the order of the beam patterns. Further, using the principles of cylindrical mode beamforming, the performance can be predicted as a function of frequency. The result is consistent with simulations in which the performance of separating music and speech sound sources was quantified.
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基于柱模波束形成估计的功率谱密度的欠定源分离
通过从一组波束形成器的输出中估计声源的功率谱密度(psd),利用维纳后滤波器可以分离声源信号。这种方法已被证明是有效的,在不确定的情况下,要分离的源的数量超过麦克风的数量。本文给出了可分离源的最大数目的一个极限,超过这个极限问题就成为秩亏问题。该研究表明,可以同时分离的源的数量与光束模式的顺序有关。此外,利用圆柱模式波束形成原理,可以预测其性能作为频率的函数。结果与对音乐声源和语音声源分离性能进行量化的仿真结果一致。
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