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An Environment-Adaptive Management Algorithm for Hearing-Support Devices Incorporating Listening Situation and Noise Type Classifiers

机译：一种包含收听情况和噪声类型分类器的听力支持设备的环境 - 自适应管理算法

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摘要

In order to provide more consistent sound intelligibility for the hearing-impaired person, regardless of environment, it is necessary to adjust the setting of the hearing-support (HS) device to accommodate various environmental circumstances. In this study, a fully automatic HS device management algorithm that can adapt to various environmental situations is proposed; it is composed of a listening-situation classifier, a noise-type classifier, an adaptive noise-reduction algorithm, and a management algorithm that can selectively turn on/off one or more of the three basic algorithms-beamforming, noise-reduction, and feedback cancellation-and can also adjust internal gains and parameters of the wide-dynamic-range compression (WDRC) and noise-reduction (NR) algorithms in accordance with variations in environmental situations. Experimental results demonstrated that the implemented algorithms can classify both listening situation and ambient noise type situations with high accuracies (92.8-96.4% and 90.9-99.4%, respectively), and the gains and parameters of the WDRC and NR algorithms were successfully adjusted according to variations in environmental situation. The average values of signal-to-noise ratio (SNR), frequency-weighted segmental SNR, Perceptual Evaluation of Speech Quality, and mean opinion test scores of 10 normal-hearing volunteers of the adaptive multiband spectral subtraction (MBSS) algorithm were improved by 1.74 dB, 2.11 dB, 0.49, and 0.68, respectively, compared to the conventional fixed-parameter MBSS algorithm. These results indicate that the proposed environment-adaptive management algorithm can be applied to HS devices to improve sound intelligibility for hearing-impaired individuals in various acoustic environments.
机译：为了为听力受损人提供更一致的声音可懂度，无论环境如何，都必须调整听力支持（HS）设备的设置，以适应各种环境情况。在本研究中，提出了一种可以适应各种环境情况的全自动HS器件管理算法;它由侦听情况分类器，噪声型分类器，自适应降噪算法和管理算法组成，可以选择性地打开/关闭三种基本算法 - 波束成形，降噪和噪声减少反馈取消 - 还可以根据环境情况的变化调整宽动态压缩（WDRC）和降噪（NR）算法的内部增益和参数。实验结果表明，实施的算法可以分类听力情况和环境噪音类型，高精度（分别为92.8-96.4％和90.9-99.4％），并根据诸如此次调整WDRC和NR算法的增益和参数环境情况的变化。发信噪比（SNR），频率加权节段SNR，语音质量评估的平均值，包括自适应多频带谱减法（MBSS）算法的10个正常听力志愿者的均值评估和平均意见测试评分与传统的固定参数MBSS算法相比，分别为1.74 dB，2.11dB，0.49和0.68。这些结果表明，所提出的环境 - 自适应管理算法可以应用于HS器件，以提高各种声学环境中听力受损个体的声音可懂度。

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