Department of Speech, Language and Hearing Sciences, Indiana University Bloomington.
Department of Speech and Hearing Sciences, University of Washington, Seattle.
Am J Audiol. 2023 Mar;32(1):197-209. doi: 10.1044/2022_AJA-22-00023. Epub 2023 Jan 27.
The signal-to-noise ratio (SNR) for speech presented in background noise may vary after being processed by digital hearing aids with nonlinear signal processing algorithms, such as wide dynamic range compression (WDRC). A phase inversion technique has been previously developed to assess the output SNR of hearing aids. However, systematic validations of this technique have not been conducted. This study aims to validate the phase inversion technique.
A simulated hearing aid with multichannel WDRC was implemented, from which the output SNRs, computed via shadow filtering, for connected speech in background noise were directly computed. The agreement between the shadow filter output SNRs and those estimated using the phase inversion technique for the same stimuli was utilized to validate the phase inversion technique. The background noise was 2- or 20-talker babble noise, and the speech stimuli were presented at SNRs of -10 to +10 dB at the input of the simulated hearing aid. The simulated hearing aid was configured to provide amplification for four representative audiograms, and the WDRC was set to be fast or slow acting. To investigate the effects of additive noise, independent of the presented noise stimulus, on the phase inversion estimated output SNR, the same simulated hearing aid was implemented with an additive Gaussian noise at its input (45 and 60 dB SPL).
Results showed that the phase inversion technique could either overestimate or underestimate output SNR, depending on the test condition; the estimation errors tended to coincide with temporal landmarks, such as natural pauses between consecutive sentences or fricatives; and increasing the simulated noise led to poorer estimates of output SNR.
Results imply that the accuracy of the phase inversion technique is dependent on the test conditions. Thus, the phase inversion technique should be used with caution, and its validity should be evaluated further.
经过具有非线性信号处理算法（如宽动态范围压缩（WDRC））的数字助听器处理后，言语在背景噪声中的信噪比（SNR）可能会发生变化。先前已经开发出相位反转技术来评估助听器的输出 SNR。然而，尚未对该技术进行系统验证。本研究旨在验证相位反转技术。
实现了具有多通道 WDRC 的模拟助听器，从中直接计算背景噪声中连接言语的输出 SNR，通过阴影滤波计算。将用于相同刺激的阴影滤波器输出 SNR 与使用相位反转技术估计的 SNR 之间的一致性用于验证相位反转技术。背景噪声为 2 或 20 人 babble 噪声，言语刺激在模拟助听器输入处的 SNR 为-10 至+10 dB。模拟助听器配置为提供四个代表性听力图的放大，WDRC 为快速或慢速作用。为了研究与呈现的噪声刺激无关的外加噪声对相位反转估计的输出 SNR 的影响，在模拟助听器的输入处添加了独立的高斯噪声（45 和 60 dB SPL）。
结果表明，相位反转技术的估计输出 SNR 可能过高或过低，这取决于测试条件；估计误差往往与时间标记相符，例如连续句子之间的自然停顿或摩擦音；增加模拟噪声会导致输出 SNR 的估计更差。
结果表明，相位反转技术的准确性取决于测试条件。因此，应谨慎使用相位反转技术，并进一步评估其有效性。
