Solving the Permutation Problem in Convolutive Blind Source Separation

Radoslaw Mazur; Alfred Mertins

doi:10.1007/978-3-540-74494-8_64

Solving the Permutation Problem in Convolutive Blind Source Separation

Institute of Signal Processing

Abstract

This paper presents a new algorithm for solving the permutation ambiguity in convolutive blind source separation. When transformed to the frequency domain, the source separation problem reduces to independent instantaneous separation in each frequency bin, which can be efficiently solved by existing algorithms. But this independency leads to the problem of correct alignment of these single bins which is still not entirely solved. The algorithm proposed in this paper models the frequency-domain separated signals using the generalized Gaussian distribution and utilizes the small deviation of the exponent between neighboring bins for the detection of correct permutations.

Original language	English
Title of host publication	Independent Component Analysis and Signal Separation
Editors	Mike E. Davies, Christopher J. James, Samer A. Abdallah, Mark D. Plumbley
Number of pages	8
Volume	4666 LNCS
Place of Publication	Berlin, Heidelberg
Publisher	Springer Berlin Heidelberg
Publication date	01.09.2007
Pages	512-519
ISBN (Print)	978-3-540-74493-1
ISBN (Electronic)	978-3-540-74494-8
DOIs	https://doi.org/10.1007/978-3-540-74494-8_64
Publication status	Published - 01.09.2007
Event	7th International Conference on Independent Component Analysis (ICA) and Source Separation - London, United Kingdom Duration: 09.09.2007 → 12.09.2007 Conference number: 70941

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10.1007/978-3-540-74494-8_64

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Mazur, R., & Mertins, A. (2007). Solving the Permutation Problem in Convolutive Blind Source Separation. In M. E. Davies, C. J. James, S. A. Abdallah, & M. D. Plumbley (Eds.), Independent Component Analysis and Signal Separation (Vol. 4666 LNCS, pp. 512-519). (Lecture Notes in Computer Science; Vol. 4666 LNCS). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-74494-8_64

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title = "Solving the Permutation Problem in Convolutive Blind Source Separation",

abstract = "This paper presents a new algorithm for solving the permutation ambiguity in convolutive blind source separation. When transformed to the frequency domain, the source separation problem reduces to independent instantaneous separation in each frequency bin, which can be efficiently solved by existing algorithms. But this independency leads to the problem of correct alignment of these single bins which is still not entirely solved. The algorithm proposed in this paper models the frequency-domain separated signals using the generalized Gaussian distribution and utilizes the small deviation of the exponent between neighboring bins for the detection of correct permutations.",

author = "Radoslaw Mazur and Alfred Mertins",

year = "2007",

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doi = "10.1007/978-3-540-74494-8_64",

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editor = "Davies, {Mike E.} and James, {Christopher J.} and Abdallah, {Samer A.} and Plumbley, {Mark D.}",

booktitle = "Independent Component Analysis and Signal Separation",

note = "7th International Conference on Independent Component Analysis (ICA) and Source Separation, ICA 2007 ; Conference date: 09-09-2007 Through 12-09-2007",

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Mazur, R & Mertins, A 2007, Solving the Permutation Problem in Convolutive Blind Source Separation. in ME Davies, CJ James, SA Abdallah & MD Plumbley (eds), Independent Component Analysis and Signal Separation. vol. 4666 LNCS, Lecture Notes in Computer Science, vol. 4666 LNCS, Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 512-519, 7th International Conference on Independent Component Analysis (ICA) and Source Separation, London, United Kingdom, 09.09.07. https://doi.org/10.1007/978-3-540-74494-8_64

Solving the Permutation Problem in Convolutive Blind Source Separation. / Mazur, Radoslaw; Mertins, Alfred.
Independent Component Analysis and Signal Separation. ed. / Mike E. Davies; Christopher J. James; Samer A. Abdallah; Mark D. Plumbley. Vol. 4666 LNCS Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. p. 512-519 (Lecture Notes in Computer Science; Vol. 4666 LNCS).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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T1 - Solving the Permutation Problem in Convolutive Blind Source Separation

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AU - Mertins, Alfred

N1 - Conference code: 70941

PY - 2007/9/1

Y1 - 2007/9/1

N2 - This paper presents a new algorithm for solving the permutation ambiguity in convolutive blind source separation. When transformed to the frequency domain, the source separation problem reduces to independent instantaneous separation in each frequency bin, which can be efficiently solved by existing algorithms. But this independency leads to the problem of correct alignment of these single bins which is still not entirely solved. The algorithm proposed in this paper models the frequency-domain separated signals using the generalized Gaussian distribution and utilizes the small deviation of the exponent between neighboring bins for the detection of correct permutations.

AB - This paper presents a new algorithm for solving the permutation ambiguity in convolutive blind source separation. When transformed to the frequency domain, the source separation problem reduces to independent instantaneous separation in each frequency bin, which can be efficiently solved by existing algorithms. But this independency leads to the problem of correct alignment of these single bins which is still not entirely solved. The algorithm proposed in this paper models the frequency-domain separated signals using the generalized Gaussian distribution and utilizes the small deviation of the exponent between neighboring bins for the detection of correct permutations.

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DO - 10.1007/978-3-540-74494-8_64

M3 - Conference contribution

SN - 978-3-540-74493-1

VL - 4666 LNCS

T3 - Lecture Notes in Computer Science

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BT - Independent Component Analysis and Signal Separation

A2 - Davies, Mike E.

A2 - James, Christopher J.

A2 - Abdallah, Samer A.

A2 - Plumbley, Mark D.

PB - Springer Berlin Heidelberg

CY - Berlin, Heidelberg

T2 - 7th International Conference on Independent Component Analysis (ICA) and Source Separation

Y2 - 9 September 2007 through 12 September 2007

ER -

Solving the Permutation Problem in Convolutive Blind Source Separation

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Blind separation of acoustic source signals in a reflective environment

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Solving the Permutation Problem in Convolutive Blind Source Separation

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Blind separation of acoustic source signals in a reflective environment

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