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Evaluation of the Influence of Head Movement on Hearing Aid Algorithm Performance Using Acoustic Simulations

机译:用声学模拟评估头部运动对助听器算法性能的影响

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Head movements can improve sound localization performance and speech intelligibility in acoustic environments with spatially distributed sources. However, they can affect the performance of hearing aid algorithms, when adaptive algorithms have to adjust to changes in the acoustic scene caused by head movement (the so-called maladaptation effect) or when directional algorithms are not facing in the optimal direction because the head has moved away (the so-called misalignment effect). In this article, we investigated the mechanisms behind these maladaptation and misalignment effects for a set of six standard hearing aid algorithms using acoustic simulations based on premade databases; this was done so we could study the effects as carefully as possible. Experiment 1 investigated the maladaptation effect by analyzing hearing aid benefit after simulated rotational head movement in simple anechoic noise scenarios. The effects of movement parameters (start angle and peak velocity), noise scenario complexity, and adaptation time were studied, as well as the recovery time of the algorithms. However, a significant maladaptation effect was only found in the most unrealistic anechoic scenario with one noise source. Experiment 2 investigated the effects of maladaptation and misalignment using previously recorded natural head movements in acoustic scenes resembling everyday life situations. In line with the results of Experiment 1, no effect of maladaptation was found in these more realistic acoustic scenes. However, a significant effect of misalignment on the performance of directional algorithms was found. This demonstrates the need to take head movement into account in the evaluation of directional hearing aid algorithms.
机译:头部运动可以在具有空间分布源的声学环境中提高声音定位性能和语音可懂性。然而,当自适应算法必须调整到由头部运动引起的声学场景(所谓的不良机效果)或者由于头部不面对最佳方向时,当由于头部不面对最佳方向时的声学场景的变化而影响助听器算法的性能已经移动了(所谓的未对准效果)。在本文中,我们调查了使用基于原始数据库的声学模拟的一组六种标准助听辅助算法对这些不适应和未对准效应的机制;这是这样做的,我们可以尽可能仔细研究效果。实验1通过在简单的化学噪声场景中分析助听器益处来研究助听器效果来研究不良效果。研究了运动参数(开始角度和峰值速度),噪声场景复杂性和适应时间的影响,以及算法的恢复时间。然而,在具有一个噪声源的最不切实际的化学学情景中仅发现了显着的不切实际的不切实际的效果。实验2研究了在类似日常生活情况的声学场景中使用先前记录的自然头部运动来调查了不对准和错位的影响。符合实验1的结果,在这些更现实的声学场景中没有发现不良的效果。然而,发现发现了对定向算法性能的显着影响。这证明了在评估方向助听辅助算法中需要考虑头部运动。

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