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Speech Noise Reduction Algorithm in Digital Hearing Aids Based on an Improved Sub-band SNR Estimation

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Abstract

To improve the speech intelligibility in noisy environments for persons with hearing impairments, a new method for reducing noise, based on improved sub-band signal-to-noise ratio (SNR) estimation, is proposed. First, the input signal is decomposed into several sub-band signals with an analysis filter bank. Then, under the assumption of a Gaussian model, maximum a posterior probability is applied to estimate the information embedded in adjacent frames in each sub-band, which is in the form of a joint probability density function, and the minimum of the noise spectrum is tracked to estimate the noise. Subsequently, the gain of each sub-band, which changes with the noise in the corresponding sub-band, is calculated with a linear proportional gain function. The obtained gains of the sub-bands are multiplied by the sub-band noisy signals to obtain the enhanced sub-band speech signals. Finally, all the sub-band signals are spliced to obtain the estimated speech signals. In this algorithm, the gains are calculated in the time domain, which avoids the process of the inverse Fourier transform and leads to a decrease in computational complexity. Compared with the traditional spectral subtraction and basic Wiener filtering method, the delay in this algorithm is reduced by 40.4 and 60.6%, respectively. It is also compared with the modulation depth integrated into hearing aids under an experimental simulation and a real scenario. The results indicate that the output SNR is improved by 1 dB under the software simulation and 3.1 dB in the real scenario when the input SNR is set as 10 dB. Compared with the simulation environment, the proposed algorithm only fell by 1.5% in the real scenario. Furthermore, the distance of the logarithmic spectrum and quality of speech perception are improved by 20.6 and 9.3%, respectively.

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Acknowledgements

The work was supported by the National Natural Science Foundation of China under Grant Nos. 61673108 and 61375028, China Postdoctoral Science Foundation funded Project under Grant No. 2016M601696, Qing Lan Project of Jiangsu Province, Six Talent Peaks Project in Jiangsu Province under Grant No. 2016-DZXX-023, Jiangsu Planned Projects for Postdoctoral Research Funds under Grant No. 1601011B, the High-level Scientific Research Foundation of NJIT under Grant No. YKJ201526 and the open fund of Guangdong lighting and audio video engineering research center under Grant Nos. KF201601 and KF201602. The authors would like to thank the reviewers for their valuable suggestions and comments.

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Authors and Affiliations

  1. School of Communication Engineering, Nanjing Institute of Technology, Nanjing, 211167, China

    Tao Jiang, Ruiyu Liang, Qinqyun Wang & Yongqiang Bao

  2. School of Information Science and Engineering, Southeast University, Nanjing, 210096, China

    Tao Jiang & Ruiyu Liang

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  1. Tao Jiang
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Correspondence to Ruiyu Liang.

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Jiang, T., Liang, R., Wang, Q. et al. Speech Noise Reduction Algorithm in Digital Hearing Aids Based on an Improved Sub-band SNR Estimation. Circuits Syst Signal Process 37, 1243–1267 (2018). https://doi.org/10.1007/s00034-017-0605-7

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