Recursive Bayesian Control of Multichannel Acoustic Echo Cancellation

Malik, Sarmad Majeed; Enzner, Gerald

doi:10.1109/lsp.2011.2166385

Cited by 35 publications

(33 citation statements)

References 12 publications

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“…Note that the same result was already obtained for the Kalman filter implementations in the DFT-domain [14,36,43].…”

Section: (C)supporting

confidence: 80%

“…• The frame shift N and the lengths of the adaptive filters K can be chosen independently of the microphone signal segment length P, as it was already described for the single-channel frequency-domain adaptive filtering algorithm [4] and for the Kalman filter implementations in the DFT-domain [14,36,43].…”

Section: Generalized Frequency-domain Adaptive Filtering Algorithmmentioning

confidence: 99%

“…This is different to [39], where only the case Q = 2P = 2K was covered. For the further derivations, is defined, where (43) and (19) can be used to verify that…”

Section: (C)mentioning

confidence: 99%

“…The GFDAF algorithm was first presented in [39], being inspired by [30,40] and incorporating concepts of [31,41,42]. Note that the Kalman filter-based approaches have also been generalized for the efficient identification of multiple-input/multiple-output systems [43].…”

Section: Introductionmentioning

confidence: 99%

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The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

Schneider

Kellermann

2016

EURASIP J. Adv. Signal Process.

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Acoustic echo cancellation (AEC) is a well-known application of adaptive filters in communication acoustics. To implement AEC for multichannel reproduction systems, powerful adaptation algorithms like the generalized frequency-domain adaptive filtering (GFDAF) algorithm are required for satisfactory convergence behavior. In this paper, the GFDAF algorithm is rigorously derived as an approximation of the block recursive least-squares (RLS) algorithm. Thereby, the original formulation of the GFDAF algorithm is generalized while avoiding an error that has been in the original derivation. The presented algorithm formulation is applied to pruned transform-domain loudspeaker-enclosure-microphone models in a mathematically consistent manner. Such pruned models have recently been proposed to cope with the tremendous computational demands of massive multichannel AEC. Beyond its generalization, a regularization of the GFDAF is shown to have a close relation to the well-known block least-mean-squares algorithm.

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“…Note that the same result was already obtained for the Kalman filter implementations in the DFT-domain [14,36,43].…”

Section: (C)supporting

confidence: 80%

Section: Generalized Frequency-domain Adaptive Filtering Algorithmmentioning

confidence: 99%

“…This is different to [39], where only the case Q = 2P = 2K was covered. For the further derivations, is defined, where (43) and (19) can be used to verify that…”

Section: (C)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

Schneider

Kellermann

2016

EURASIP J. Adv. Signal Process.

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show abstract

“…The alternative approach in [6] relies on an acoustic state-space model of the echo path to deduce a robust and efficient frequency-domain adaptive filter with inherent step-size control, however, not considering block partitioning. This approach has analogously been applied to multichannel as well as nonlinear adaptive filtering problems [20,21]. In this paper, we extend the approach in [6] to the partitioned-block filtering structure, which is of practical importance for the application of AECs for widely varying acoustic conditions.…”

Section: Introduction and Relation To Prior Workmentioning

confidence: 99%

State-space architecture of the partitioned-block-based acoustic echo controller

Kuech

Mabande

Enzner

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Acoustic echo cancellation has traditionally employed basically all variants known from deterministic adaptive filter design, such as least mean-square (LMS), recursive least-squares (RLS), and frequency-domain adaptive filters (FDAF). More recently, a stochastic adaptive filter design based on the concept of acoustic state-space modeling of the echo path has been introduced to accommodate for an ever sought unification of adaptive filtering and adaptation control. The corresponding Kalman filter theory has been formulated for single-channel, multi-channel, and nonlinear echo cancellation problems. This paper closes an important gap by formulating the state-space model and the corresponding adaptive algorithm for the partitioned-block filtering structure which is especially relevant in practice. This structure allows for the use of significantly longer filter lengths in comparison to previous work, and for the flexible design and implementation of acoustic echo cancellers for widely differing acoustic conditions.

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A Deep Hybrid Model for Stereophonic Acoustic Echo Control

Liu,

Yang

et al. 2024

Circuits Syst Signal Process

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Recursive Bayesian Control of Multichannel Acoustic Echo Cancellation

Cited by 35 publications

References 12 publications

The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

State-space architecture of the partitioned-block-based acoustic echo controller

A Deep Hybrid Model for Stereophonic Acoustic Echo Control

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