#3721. Retraction notice to “Multi-channel adaptive loudness compensation algorithm based on noise tracking in digital hearing aids” [Measurement 130C (20XX) 2773] (Speech Communication (20XX) 130 (64–76), (S0167639321000406), (10.1016/j.specom.20XX.04.002))

October 2026publication date
Proposal available till 08-06-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Language and Linguistics;
Linguistics and Language;
Communication;
Modeling and Simulation;
Computer Science Applications;
Computer Vision and Pattern Recognition;
Software;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
The existing loudness compensation algorithms in digital hearing aids destroy the formant structure of the speech signal easily. As a result, the output speech signal fails to meet the requirements of hearing-impaired (HI) people. To solve these problems, a novel multi-channel adaptive loudness compensation algorithm which can vary according to signal-to-noise ratio (SNR) is proposed. In this algorithm, signals are first divided into multiple frequency bands by the Gammatone filter banks that protect the formant structure. Then, binary masked speech enhancement based on human auditory characteristics is implemented in each frequency band, removing noise as much as possible while maintaining the authenticity of speech. Essentially, we propose an adaptive loudness compensation coefficient which can vary referring to the SNR, and adaptively adjust the weight of both the linear compensation and the wide dynamic compression in different frequency bands. The experimental results have shown that compared with the contrast algorithm, the proposed algorithm not only effectively protects the formant of speech in the noise environment, but also suppresses the influence of noise on the loudness performances, along with improvements in intelligibility, comfort level and the clarity of the speech.
Keywords:
loudness compensation algorithms; speech enhancement; output speech signal; hearing-impaired (HI) people

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