An all-frequency-domain adaptive filter with PEM-based decorrelation for acoustic feedback control

Bernardi, Giuliano; Waterschoot, Toon van; Wouters, Jan; Moonen, Marc

doi:10.1109/waspaa.2015.7336931

Cited by 11 publications

(12 citation statements)

References 12 publications

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“…This algorithm was initially developed in [5] and it provides estimates of both the feedback path and the desired speech signal model in ( 1) and (3), respectively. The implemented algorithm is the frequencydomain version presented in [16] (the reader is referred to [16] for a detailed explanation of the AFC algorithm). The input signals of the AFC algorithm are the noisy loudspeaker signal and the estimate of the total contribution of s and us in the reference microphone, u and xrs, respectively.…”

Section: Afc Stagementioning

confidence: 99%

“…In the AFC stage a single-channel so-called PEM-AFROW algorithm is used. The implemented algorithm is the frequency-domain version presented in [16] (the reader is referred to [16] for a detailed explanation of the AFC algorithm). The input signals of the AFC algorithm are ûs and ŷrs.…”

Section: Afc Stagementioning

confidence: 99%

“…This allows to estimate a rank-2 (M + 1)-MWF in the NR stage [13] which is then used to obtain estimates of the speech component in the reference microphone and in the loudspeaker signal. These estimates are later used in a single-channel prediction-error method (PEM) based AFC [5,16].…”

Section: Introductionmentioning

confidence: 99%

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Cascade Multi-Channel Noise Reduction and Acoustic Feedback Cancellation

Ruiz

Waterschoot

Moonen

2022

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Acoustic feedback and noise are common problems that corrupt microphone signals and affect the performance of speech and audio signal processing applications and devices. In this paper, a cascade noise reduction (NR) and acoustic feedback cancellation (AFC) algorithm is presented for speech applications where a multi-channel Wiener filter (MWF) based NR is applied first followed by a singlechannel prediction-error method (PEM) based adaptive feedback cancellation stage. It is shown that by using a rank-2 estimate of the speech correlation matrix in the NR stage it is possible to obtain a good feedback path estimate for the reference microphone in the AFC stage. Closed-loop simulations with M microphones and 1 loudspeaker are presented using both an M -channel rank-1 and an (M + 1)-channel rank-2 MWF and it is shown that for the considered input signal-to-noise ratios the proposed algorithm increases the added stable gain (ASG) of the system.

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Section: Afc Stagementioning

confidence: 99%

Section: Afc Stagementioning

confidence: 99%

See 1 more Smart Citation

Cascade Multi-Channel Noise Reduction and Acoustic Feedback Cancellation

Ruiz

Waterschoot

Moonen

2022

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…To reduce this bias, multiple decorrelation methods have been investigated in literature, e.g., delay insertion [1,5], probe noise insertion [6][7][8][9], frequency shifting [10,11], phase modulation [12], and pre-whitening filters [13,14]. Among those methods, prediction error method based adaptive feedback cancellation (PEM-AFC) is well established as it can be effectively applied in both the time domain [14][15][16][17][18][19] and the frequency domain [2,[20][21][22][23][24]. In this method, the input signals of an adaptive filter were pre-whitened by using prefilters, resulting in lower correlation and so bias.…”

Section: Introductionmentioning

confidence: 99%

A Switched Algorithm for Adaptive Feedback Cancellation Using Pre-Filters in Hearing Aids

Tran¹,

Nordholm

2021

Audiology Research

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Acoustic coupling between microphone and loudspeaker is a significant problem in open-fit digital hearing aids. An open-fit compared to a close-fit hearing aid significantly lowers the signal quality and limits the achievable maximum stable gain. Adaptive feedback cancellation (AFC) enables an efficient approach to reduce the impact of acoustic coupling. However, without careful consideration, it can also introduce bias in estimating the feedback path due to the high correlation between the loudspeaker signal and the incoming signal, especially when the incoming signal is spectrally coloured, e.g., speech and music. The prediction error method (PEM) is well known for reducing this bias. The presented study aims to propose a switched PEM with soft-clipping (swPEMSC) that allows for further improvement in convergence/tracking rates, resulting in a better ability to recover from unstable/howling status. This swPEMSC employs a new update rule inspired by a soft-clipping based stability detector (SCSD). It allows to pick up either the PEMSC-NLMS or PEMSC-APA depending on the magnitude of the effective feedback signal; howling corresponds to a large feedback signal. The PEMSC-NLMS with a small step-size ensures a low steady-state error, but slow convergence/tracking rates, while PEMSC-APA with a large step-size allows for fast convergence/tracking rates, but a high steady-state error. By combining those approaches, the proposed approach can take advantage of good characteristics from both. Experimental results using different types of incoming signals and an abrupt change of feedback paths show that the swPEMSC can shorten unstable periods (howling) by improving the convergence and tracking rates while retaining a low steady-state error and good signal quality.

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“…To reduce the negative effect of the acoustic feedback problem, a modern approach is to use adaptive filters in a system identification setup. Some examples of using the adaptive filters can be found in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

A Method for Determining Periodically Time-Varying Bias and Its Applications in Acoustic Feedback Cancellation

Guo

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Adaptive filters have been widely used for feedback cancellation in audio systems including hearing aids. In addition to adaptive filters, the frequency shifting has often been used to obtain an unbiased estimation of the adaptive filters, by decorrelating the incoming and outgoing signals of the audio system. However, it has been shown in a recent study, that although the frequency shifting technique is effective in decorrelating the signals, its use in addition to the adaptive filter would introduce an additional and signal dependent periodically time-varying bias also referred to as the residual bias, especially for tonal signals such as music. In this work, we make use of that knowledge and propose a method to detect different acoustic situations, based on the level of residual bias. We further discuss on some control actions to be taken in acoustic feedback cancellation systems upon these detections. Finally, we demonstrate the behavior of the residual bias and the detection of different acoustic feedback situations in an example computer simulation.

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An all-frequency-domain adaptive filter with PEM-based decorrelation for acoustic feedback control

Cited by 11 publications

References 12 publications

Cascade Multi-Channel Noise Reduction and Acoustic Feedback Cancellation

Cascade Multi-Channel Noise Reduction and Acoustic Feedback Cancellation

A Switched Algorithm for Adaptive Feedback Cancellation Using Pre-Filters in Hearing Aids

A Method for Determining Periodically Time-Varying Bias and Its Applications in Acoustic Feedback Cancellation

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