Acoustic source separation of convolutive mixtures based on intensity vector statistics

Date

2008-05-01

Author

Günel Kılıç, Banu
Hacıhabiboğlu, Hüseyin

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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 microphone array. No assumptions are made on the signals, but it is assumed that the source directions are known a priori. Directivity functions based on von Mises functions are designed for beamforming depending on the circular statistics of the calculated intensity vectors. Numerical evaluation results were presented for various speech and instrument sounds and source positions in two reverberant rooms.

Subject Keywords

Array processing, B-format, Beamforming, Circular statistics, Coincident microphone array, Convolutive mixtures, Intensity, Source separation

URI

https://hdl.handle.net/11511/32309

Journal

IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING

DOI

https://doi.org/10.1109/tasl.2008.918967

Collections

Graduate School of Informatics, Article

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Citation Formats

B. Günel Kılıç and H. Hacıhabiboğlu, “Acoustic source separation of convolutive mixtures based on intensity vector statistics,” IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, pp. 748–756, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32309.