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TASLP
2008

Acoustic Source Separation of Convolutive Mixtures Based on Intensity Vector Statistics

8 years 12 months ago
Acoustic Source Separation of Convolutive Mixtures Based on Intensity Vector Statistics
Various techniques have previously been proposed for the separation of convolutive mixtures. These techniques can be classified as stochastic, adaptive, and deterministic. Stochastic methods are computationally expensive since they require an iterative process for the calculation of the demixing filters based on a separation criterion that usually assumes that the source signals are statistically independent. Adaptive methods, such as the adaptive beamformers, also exploit signal properties in order to optimize a multichannel filter structure. However, these algorithms need initialization and time to converge. Deterministic methods, on the other hand, provide a closed-form solution based on the deterministic aspects of the problem, such as the channel characteristics and the source directions. This paper presents a technique that exploits the intensity vector statistics to achieve a nearly closed-form solution for the separation of the convolutive mixtures as recorded with a coincident...
Banu Gunel, Hüseyin Hacihabiboglu, Ahmet M. K
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TASLP
Authors Banu Gunel, Hüseyin Hacihabiboglu, Ahmet M. Kondoz
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