Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm

S. Goetze; M. Kallinger; A. Mertins; K. Kammeyer

doi:10.1109/ACSSC.2008.5074522

Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm

S. Goetze, M. Kallinger, A. Mertins, K. Kammeyer

Institute of Signal Processing

Abstract

Dereverberation of speech signals in a hands-free scenario by inverse filtering has been a research topic for several years now. However, it is still a challenging problem because of the nature of common room impulse responses (RIRs), which are time-variant mixed phase systems having a large number of zeros close to, on, and even outside the unit circle in the z-domain. In this contribution an adaptive multi-channel equalization algorithm based on a decoupled version of the modified filtered-X LMS (mFxLMS) will be derived in the partitioned frequency domain. This new algorithm allows for fast convergence, computationally efficient implementation, and a low system delay under realistic conditions such as ambient noise and imperfect RIR estimates.

Original language	English
Title of host publication	2008 42nd Asilomar Conference on Signals, Systems and Computers
Number of pages	5
Publisher	IEEE
Publication date	01.10.2008
Pages	811-815
ISBN (Print)	978-1-4244-2940-0
ISBN (Electronic)	978-1-4244-2941-7
DOIs	https://doi.org/10.1109/ACSSC.2008.5074522
Publication status	Published - 01.10.2008
Event	2008 42nd Asilomar Conference on Signals, Systems and Computers - Pacific Grove, United States Duration: 26.10.2008 → 29.10.2008 Conference number: 77519

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10.1109/ACSSC.2008.5074522

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@inproceedings{9861a98b192641f0a22432b505644042,

title = "Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm",

abstract = "Dereverberation of speech signals in a hands-free scenario by inverse filtering has been a research topic for several years now. However, it is still a challenging problem because of the nature of common room impulse responses (RIRs), which are time-variant mixed phase systems having a large number of zeros close to, on, and even outside the unit circle in the z-domain. In this contribution an adaptive multi-channel equalization algorithm based on a decoupled version of the modified filtered-X LMS (mFxLMS) will be derived in the partitioned frequency domain. This new algorithm allows for fast convergence, computationally efficient implementation, and a low system delay under realistic conditions such as ambient noise and imperfect RIR estimates.",

author = "S. Goetze and M. Kallinger and A. Mertins and K. Kammeyer",

year = "2008",

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doi = "10.1109/ACSSC.2008.5074522",

language = "English",

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series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

publisher = "IEEE",

pages = "811--815",

booktitle = "2008 42nd Asilomar Conference on Signals, Systems and Computers",

note = "2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008 ; Conference date: 26-10-2008 Through 29-10-2008",

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Goetze, S, Kallinger, M, Mertins, A & Kammeyer, K 2008, Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm. in 2008 42nd Asilomar Conference on Signals, Systems and Computers. Conference Record - Asilomar Conference on Signals, Systems and Computers, IEEE, pp. 811-815, 2008 42nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, United States, 26.10.08. https://doi.org/10.1109/ACSSC.2008.5074522

Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm. / Goetze, S.; Kallinger, M.; Mertins, A. et al.
2008 42nd Asilomar Conference on Signals, Systems and Computers. IEEE, 2008. p. 811-815 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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

TY - GEN

T1 - Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm

AU - Goetze, S.

AU - Kallinger, M.

AU - Mertins, A.

AU - Kammeyer, K.

N1 - Conference code: 77519

PY - 2008/10/1

Y1 - 2008/10/1

N2 - Dereverberation of speech signals in a hands-free scenario by inverse filtering has been a research topic for several years now. However, it is still a challenging problem because of the nature of common room impulse responses (RIRs), which are time-variant mixed phase systems having a large number of zeros close to, on, and even outside the unit circle in the z-domain. In this contribution an adaptive multi-channel equalization algorithm based on a decoupled version of the modified filtered-X LMS (mFxLMS) will be derived in the partitioned frequency domain. This new algorithm allows for fast convergence, computationally efficient implementation, and a low system delay under realistic conditions such as ambient noise and imperfect RIR estimates.

AB - Dereverberation of speech signals in a hands-free scenario by inverse filtering has been a research topic for several years now. However, it is still a challenging problem because of the nature of common room impulse responses (RIRs), which are time-variant mixed phase systems having a large number of zeros close to, on, and even outside the unit circle in the z-domain. In this contribution an adaptive multi-channel equalization algorithm based on a decoupled version of the modified filtered-X LMS (mFxLMS) will be derived in the partitioned frequency domain. This new algorithm allows for fast convergence, computationally efficient implementation, and a low system delay under realistic conditions such as ambient noise and imperfect RIR estimates.

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U2 - 10.1109/ACSSC.2008.5074522

DO - 10.1109/ACSSC.2008.5074522

M3 - Conference contribution

SN - 978-1-4244-2940-0

T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers

SP - 811

EP - 815

BT - 2008 42nd Asilomar Conference on Signals, Systems and Computers

PB - IEEE

T2 - 2008 42nd Asilomar Conference on Signals, Systems and Computers

Y2 - 26 October 2008 through 29 October 2008

ER -

Multi-channel listening-room compensation using a decoupled filtered-X LMS algorithm

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