Joint noise reduction and acoustic echo cancellation using the transfer-function generalized sidelobe canceller

Gal, Reuven; Gannot, Sharon; Cohen, Israel

doi:10.1016/j.specom.2006.12.008

Cited by 31 publications

(14 citation statements)

References 22 publications

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“…Alternative structures that have been proposed include the use of polynomial approximations in delay-and-sum beamformers [24], [25], the Transfer-Function Generalized Sidelobe Canceler (TF-GSC) [26]- [29], AEC sub-modeling [30], mutually exclusive adaptation of the BF and AEC [31] and wave-domain filtering [32], [33].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of a Jointly Optimized Beamformer-Assisted Acoustic Echo Canceler

Maruo

Bermudez

Resende

2014

IEEE Trans. Signal Process.

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This work presents a statistical analysis of a class of jointly optimized beamformer-assisted acoustic echo cancelers (AEC) with the beamformer (BF) implemented in the Generalized Sidelobe Canceler (GSC) form and using the least-mean square (LMS) algorithm. The analysis considers the possibility of independent convergence control for the BF and the AEC. The resulting models permit the study of system performance under typical handling of double-talk and channel changes. We show that the joint optimization of the BF-AEC is equivalent to a linearly-constrained minimum variance problem. Hence, the derived analytical model can be used to predict the transient performance of general adaptive wideband beamformers. We study the transient and steady-state behaviors of the residual mean echo power for stationary Gaussian inputs. A convergence analysis leads to stability bounds for the step-size matrix and design guidelines are derived from the analytical models. Monte Carlo simulations illustrate the accuracy of the theoretical models and the applicability of the proposed design guidelines. Examples include operation under mild degrees of nonstationarity. Finally, we show how a high convergence rate can be achieved using a quasi-Newton adaptation scheme in which the step-size matrix is designed to whiten the combined input vector.Index Terms-Acoustic echo cancellation, adaptive filtering, beamforming, generalized sidelobe canceller, statistical analysis

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Section: Introductionmentioning

confidence: 99%

Statistical Analysis of a Jointly Optimized Beamformer-Assisted Acoustic Echo Canceler

Maruo

Bermudez

Resende

2014

IEEE Trans. Signal Process.

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“…Recent approaches try to reduce the complexity of the AEC-first structure by exploiting similarities across channels for the adaptation control and design of the multi-microphone AEC [4], [5]. There also exist approaches that focus on enhancing the AEC adaptation by BF rather than reducing the complexity [6].…”

Section: Introductionmentioning

confidence: 99%

Change Prediction for Low Complexity Combined Beamforming and Acoustic Echo Cancellation

Schrammen

Bohlender

Kühl

et al. 2019

2019 27th European Signal Processing Conference (EUSIPCO)

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Time-variant beamforming (BF) and acoustic echo cancellation (AEC) are two techniques that are frequently employed for improving the quality of hands-free speech communication. However, the combined application of both is quite challenging as it either introduces high computational complexity or insufficient tracking. We propose a new method to improve the performance of the low-complexity beamformer first (BF-first) structure, which we call change prediction (ChaP). ChaP gathers information on several BF changes to predict the effective impulse response seen by the AEC after the next BF change. To account for uncertain data and convergence states in the predictions, reliability measures are introduced to improve ChaP in realistic scenarios.Index Terms-combined beamforming and acoustic echo cancellation, low complexity, beamformer first, pseudo inverse

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“…Echo cancellation is used in many fields of acoustics , such as hands‐free applications , video conferencing , digital multimedia broadcasting , satellite networking , and hearing aids . The adaptive echo cancellation algorithm has been widely studied because of its good adaptability to the environment.…”

Section: Introductionmentioning

confidence: 99%

A joint echo cancellation algorithm for quick suppression of howls in hearing aids

Liang

Wang

et al. 2017

IEEJ Transactions Elec Engng

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When the echo path of a hearing aid suddenly changes, howls easily occur. To quickly suppress the howls, a joint echo cancellation (JEC) algorithm, which combines the variable step normalized least mean square (VNLMS) algorithm with the notch filter algorithm, is proposed. According to whether the hearing aid howls or not, different strategies are used. First, when there are no howls, the echo signal is estimated using VNLMS and the step factor is computed according to three types of filter states, which are defined based on the normalized distance between the short-term average and the long-term average of the filter coefficients. Then, different step factors are used for different states. Second, when there are howls, the update of VNLMS is frozen to stabilize the howl frequency. To improve the detection accuracy, a howling detection algorithm based on the zoom-fast Fourier transformation (ZoomFFT) is proposed. The ZoomFFT algorithm can analyze the spectrum of a narrowband signal in a specified high sampling frequency. Then, the notch filters based on the estimated howl frequencies are dynamically generated to restrain the howls. Finally, when the howls are suppressed, VNLMS is reactivated. Compared to other echo cancellation algorithms, the proposed algorithm can quickly suppress the howls, and JEC has the best comprehensive performance. Furthermore, the quality of the processed speech is high, and the operation time is short. Thus, the proposed algorithm is suitable for low-power-consumption and small-volume products such as hearing aids.

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Joint noise reduction and acoustic echo cancellation using the transfer-function generalized sidelobe canceller

Cited by 31 publications

References 22 publications

Statistical Analysis of a Jointly Optimized Beamformer-Assisted Acoustic Echo Canceler

Statistical Analysis of a Jointly Optimized Beamformer-Assisted Acoustic Echo Canceler

Change Prediction for Low Complexity Combined Beamforming and Acoustic Echo Cancellation

A joint echo cancellation algorithm for quick suppression of howls in hearing aids

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