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Effect of Energy Equalization on the Intelligibility of Speech in Fluctuating Background Interference for Listeners With Hearing Impairment

机译:能量平衡对听觉受损听众波动背景干扰中语音清晰度的影响

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摘要

The masking release (MR; i.e., better speech recognition in fluctuating compared with continuous noise backgrounds) that is evident for listeners with normal hearing (NH) is generally reduced or absent for listeners with sensorineural hearing impairment (HI). In this study, a real-time signal-processing technique was developed to improve MR in listeners with HI and offer insight into the mechanisms influencing the size of MR. This technique compares short-term and long-term estimates of energy, increases the level of short-term segments whose energy is below the average energy, and normalizes the overall energy of the processed signal to be equivalent to that of the original long-term estimate. This signal-processing algorithm was used to create two types of energy-equalized (EEQ) signals: EEQ1, which operated on the wideband speech plus noise signal, and EEQ4, which operated independently on each of four bands with equal logarithmic width. Consonant identification was tested in backgrounds of continuous and various types of fluctuating speech-shaped Gaussian noise including those with both regularly and irregularly spaced temporal fluctuations. Listeners with HI achieved similar scores for EEQ and the original (unprocessed) stimuli in continuous-noise backgrounds, while superior performance was obtained for the EEQ signals in fluctuating background noises that had regular temporal gaps but not for those with irregularly spaced fluctuations. Thus, in noise backgrounds with regularly spaced temporal fluctuations, the energy-normalized signals led to larger values of MR and higher intelligibility than obtained with unprocessed signals.
机译:对于具有正常听觉(NH)的听众来说,掩盖释放(MR;即,与连续噪声背景相比,在波动中具有更好的语音识别)通常对于感觉神经性听觉障碍(HI)的听众而言是减少或不存在的。在这项研究中,开发了一种实时信号处理技术来改善HI听众的MR,​​并深入了解影响MR大小的机制。该技术比较能量的短期和长期估计,增加能量低于平均能量的短期片段的水平,并将处理后的信号的总能量归一化以等于原始长期能量估计。此信号处理算法用于创建两种类型的能量均衡(EEQ)信号:EEQ1(对宽带语音加噪声信号进行操作)和EEQ4(对等宽度对等的四个频带中的每个频带独立进行操作)。在连续和各种类型的波动语音形状的高斯噪声(包括具有规则和不规则间隔时间波动的噪声)的背景下测试了辅音识别。 HI的听众在连续噪声背景中获得了EEQ和原始(未处理)刺激相似的分数,而EEQ信号在波动的背景噪声中具有卓越的表现,这些噪声具有规则的时间间隔,但对于不规则间隔的波动则没有。因此,在具有规则间隔的时间波动的噪声背景中,与未处理的信号相比,能量归一化的信号导致更大的MR值和更高的清晰度。

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