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Howling Detection and Suppression Based on Segmented Notch Filtering

The existing adaptive echo cancellation based howling (typically in hearing aids) removal methods have several drawbacks such as insufficient attenuation of the howling component, slow response and nonlinear distortion. To solve these problems, we propose a segmented notch filtering based scheme. Sp...

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Detalles Bibliográficos
Autores principales: Li, Yanping, Huang, Xiangdong, Zheng, Yi, Gao, Zhongke, Kou, Lei, Wan, Junhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659983/
https://www.ncbi.nlm.nih.gov/pubmed/34884065
http://dx.doi.org/10.3390/s21238062
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author Li, Yanping
Huang, Xiangdong
Zheng, Yi
Gao, Zhongke
Kou, Lei
Wan, Junhe
author_facet Li, Yanping
Huang, Xiangdong
Zheng, Yi
Gao, Zhongke
Kou, Lei
Wan, Junhe
author_sort Li, Yanping
collection PubMed
description The existing adaptive echo cancellation based howling (typically in hearing aids) removal methods have several drawbacks such as insufficient attenuation of the howling component, slow response and nonlinear distortion. To solve these problems, we propose a segmented notch filtering based scheme. Specifically, firstly, it is proved that the attenuation value can reach [Formula: see text] dB at any detected howling frequency; secondly, the filter coefficients can be readily calculated by a closed-form formula, yielding a fast response to the sudden howling accident; thirdly, the closed-form formula of this filter is theoretically an even function, indicating that this filter possesses a linear transfer characteristic. In combination with proper segmentation and precisely removing these transient samples arising from FIR (Finite Impulsive Response) filtering, nonlinear distortion can be entirely avoided. Experimental results show that our proposed scheme can not only accurately estimate the howling frequency, but can also completely remove it, which yields a high-quality output waveform with a recovery SNR of about 22 dB. Therefore, the proposed segmented notching based scheme possesses vast potential for hearing aid development and other relevant applications.
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spelling pubmed-86599832021-12-10 Howling Detection and Suppression Based on Segmented Notch Filtering Li, Yanping Huang, Xiangdong Zheng, Yi Gao, Zhongke Kou, Lei Wan, Junhe Sensors (Basel) Article The existing adaptive echo cancellation based howling (typically in hearing aids) removal methods have several drawbacks such as insufficient attenuation of the howling component, slow response and nonlinear distortion. To solve these problems, we propose a segmented notch filtering based scheme. Specifically, firstly, it is proved that the attenuation value can reach [Formula: see text] dB at any detected howling frequency; secondly, the filter coefficients can be readily calculated by a closed-form formula, yielding a fast response to the sudden howling accident; thirdly, the closed-form formula of this filter is theoretically an even function, indicating that this filter possesses a linear transfer characteristic. In combination with proper segmentation and precisely removing these transient samples arising from FIR (Finite Impulsive Response) filtering, nonlinear distortion can be entirely avoided. Experimental results show that our proposed scheme can not only accurately estimate the howling frequency, but can also completely remove it, which yields a high-quality output waveform with a recovery SNR of about 22 dB. Therefore, the proposed segmented notching based scheme possesses vast potential for hearing aid development and other relevant applications. MDPI 2021-12-02 /pmc/articles/PMC8659983/ /pubmed/34884065 http://dx.doi.org/10.3390/s21238062 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Yanping
Huang, Xiangdong
Zheng, Yi
Gao, Zhongke
Kou, Lei
Wan, Junhe
Howling Detection and Suppression Based on Segmented Notch Filtering
title Howling Detection and Suppression Based on Segmented Notch Filtering
title_full Howling Detection and Suppression Based on Segmented Notch Filtering
title_fullStr Howling Detection and Suppression Based on Segmented Notch Filtering
title_full_unstemmed Howling Detection and Suppression Based on Segmented Notch Filtering
title_short Howling Detection and Suppression Based on Segmented Notch Filtering
title_sort howling detection and suppression based on segmented notch filtering
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659983/
https://www.ncbi.nlm.nih.gov/pubmed/34884065
http://dx.doi.org/10.3390/s21238062
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