Evidence map›Paper›PMID 34884065›Full record

ArticleSensors (Basel, Switzerland)2021

Howling Detection and Suppression Based on Segmented Notch Filtering.

Yanping Li, Xiangdong Huang, Yi Zheng, Zhongke Gao, Lei Kou, Junhe Wan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yanping LiSchool of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.
Xiangdong HuangSchool of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.ORCID 0000-0003-1217-3809
Yi ZhengInstitute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), 37 Miaoling Road, Qingdao 266000, China.
Zhongke GaoSchool of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.
Lei KouInstitute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), 37 Miaoling Road, Qingdao 266000, China.ORCID 0000-0002-9756-2805
Junhe WanInstitute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), 37 Miaoling Road, Qingdao 266000, China.ORCID 0000-0003-0206-2742

Funding

National Natural Science Foundation of China 61671012
6 · The paper itself

Abstract

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 -330 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.

Indexed as

Hearing Aidscenter frequency controlFIR notch filterhowling detectionhowling suppression

Identifiers

PMID34884065
PMCPMC8659983

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