Feedback cancellation in digital hearing aids using convex combination of proportionate adaptive algorithms

Vanamadi, Ravi; Kar, Asutosh

doi:10.1016/j.apacoust.2021.108175

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…The MIS is the measure of how much the estimated AF path deviates from the actual AF path in the frequency domain, and the ASG is the amount of additional gain transferred to the device after performing AFC [1], [4], [7]. Therefore, in AFC applications, to design a high-performance AFC system, lower MIS and higher ASG values are necessary [4], [7].…”

Section: Table I: the Pseudo-code Of Pn-oc-lms Based Afc Systemmentioning

confidence: 99%

“…The AF limits the maximum available power of the hearing aids and it causes instability in the system. As the AF causes buzzing in the ear, it disturbs the user [1], [2]. Adaptive filtering is a common method used as an acoustic feedback canceller (AFC) [3].…”

Section: Introductionmentioning

confidence: 99%

“…In general terms, adaptive filtering-based AFC works by removing the estimated feedback signal from the microphone input [3]. In AFC applications including the adaptive filter, the AF path is usually modeled with a finite impulse response (FIR) filter structure [1]. To update the weight coefficients of the FIR filter, the least mean square (LMS), normalized LMS (normalized LMS, NLMS), and recursive least square (RLS) algorithms are frequently used [4], [5], [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

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An acoustic feedback canceler based on probe noise and informative data for hearing aids

Eren,

Güvenç,

Mengüç

2023

SIViP

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One of the important issues encountered in acoustic feedback canceller (AFC) systems is the bias occurring in the estimation of the acoustic feedback (AF) path. In the literature, a common solution is to inject the probe noise into the loudspeaker to reduce the correlation between the input signal and the loudspeaker signal, that is, to remove the bias occurring in the estimation of the AF path. This approach significantly improves the performance of the AFC systems. However, when considering high filter orders and large-scale input signals, such systems designed by probe noise injection suffer from the data processing cost, and thus their real-time implementations on a chip generally become challenging.To this end, in this paper, we propose an AFC system using jointly probe noise and informative data, named the probe noise-online censoring-least mean square (PN-OC-LMS) based AFC. Thanks to both the OC mechanism and the probe noise injection approach, the proposed PN-OC-LMS based AFC system significantly not only reduces the data processing cost but also effectively removes the bias effect in the AF path. The mentioned effectiveness of the proposed AFC system is supported by two comprehensive different experiments on a real-world AF path measured from a behind-the-ear hearing aid. As a result, in the proposed AFC system, the use of both informative data and the injection of probe noise will enable the design of a long-term working wearable hearing aid device that provides low data processing cost and correctly estimates the AF path.

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Section: Table I: the Pseudo-code Of Pn-oc-lms Based Afc Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An acoustic feedback canceler based on probe noise and informative data for hearing aids

Eren,

Güvenç,

Mengüç

2023

SIViP

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“…The amplified signal returns to the microphone in hearing aids on a path, which is called the AF path. The AF limits the maximum achievable gain by causing system instability, while at the same time creating discomfort in the user due to the fact that it causes howling in the ear [4], [5].…”

Section: Introductionmentioning

confidence: 99%

“…The main purpose of adaptive filtering is to predict the AF path in an online manner and then extract the predicted feedback signal from the microphone input to obtain the signal in which the feedback effect is reduced [6]. In the literature, the AF is usually modeled by the finite impulse response (FIR) filter structure, and the least mean square (LMS) algorithm is generally preferred to update the weight coefficients of the FIR filter due to its simple computational complexity and robustness in many applications [4]. Owing to the closed-loop structure of hearing aids, there may be a high correlation between the source signal and the loudspeaker signal, and this situation may cause bias in the estimation of the AF path [5], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Cost-Effective Acoustic Feedback Cancellers for Digital Hearing Aids

Eren,

Güvenç,

Mengüç

2024

IEEE/ACM Trans. Audio Speech Lang. Process.

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To mitigate the bias caused by the strong correlation between the loudspeaker and source signals in the acoustic feedback (AF) canceller (AFC), the prediction error method (PEM) based AFC (PEMAFC) is the most popular solution but comes with two inherent drawbacks. Firstly, to improve the tracking performance of the PEM filter in the processing of nonstationary signals such as speech and music, the recursive least square (RLS) algorithm is commonly used, but this leads to unmanageable computational complexity in the PEMAFC system. Secondly, though the decorrelated least mean square (DLMS) algorithm is often preferred as an update algorithm for estimating the AF path due to its simple structure, it still suffers from inferior steady-state performance. By drawing inspiration from the online censoring (OC) strategy that has significantly contributed to the adaptive processing of big data streams, we develop two PEMAFC systems in this paper, called OC-PEMAFC-1 and OC-PEMAFC-2. The OC-PEMAFC-1 employs the OC-RLS algorithm to update the weight vector of the PEM filter and shows a comparable performance by considerably reducing the overall computational complexity of the PEMAFC arising from the classical RLS. On the contrary, the OC-PEMAFC-2 incorporates the OC-DLMS algorithm using only informative data streams, thus substantially enhancing the steady-state performance and partially reducing the overall computational complexity of the PEMAFC. This also study provides the stability analyses of the OC-RLS and OC-DLMS used in the proposed PEMAFC systems. The mentioned superiorities of the proposed systems are confirmed through simulation results on real-world feedback paths.

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Review on Recent Advances in Hearing Aids: A Signal Processing Perspective

Devi

VASUNDHARA

2023

Algorithms for Intelligent Systems

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Feedback cancellation in digital hearing aids using convex combination of proportionate adaptive algorithms

Cited by 9 publications

References 15 publications

An acoustic feedback canceler based on probe noise and informative data for hearing aids

An acoustic feedback canceler based on probe noise and informative data for hearing aids

Cost-Effective Acoustic Feedback Cancellers for Digital Hearing Aids

Review on Recent Advances in Hearing Aids: A Signal Processing Perspective

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