Masking release in hearing loss: cochlear compression and effective audibility

描述(申请人提供)：与听力敏感度正常的听者相比，感音神经性听力损失的听者经历更多的掩蔽，而从掩蔽中释放的明显更少。当背景噪声是间歇性的时，正常听力(NH)听者利用噪声中的瞬时凹陷来理解目标信号。这种益处被称为掩蔽释放(MR)。听力受损(HI)的听众不会经历与NH听众相同程度的MR。因此，在噪声环境中，高音听者不能在相同的信噪比下理解语音。与此同时，听力受损的听众经常抱怨他们的扩音设备在背景噪音中不能令人满意。我们建议加深对听力损失听者所经历的掩蔽和MR的理解，并调查其原因和潜在的补救来源。在实验1中，我们将在各种噪声、信号电平和带宽的语音识别实验中测试MR。我们将测试NH和HI监听者，以及其阈值将被噪声提高以匹配HI监听者的NH监听者。我们将测量听者在安静噪声、稳定噪声和波动噪声下的句子识别，并将MR定义为稳定噪声和波动噪声之间的表现差异。我们基于初步结果假设，信号的可听性不能完全解释HI听者MR降低的原因，并且HI听者在噪声下降时获得关于语音的频谱信息的机会减少可以解释额外的变异性。我们进一步假设，在间歇性噪声条件下，耳蜗人的基本生理变化可以解释听力障碍者的困难，我们建议在实验2中测量耳蜗功能。我们将通过测量基底膜输入/输出反应、掩蔽周期模式、调制掩蔽和频率选择性来描述听力障碍者的耳蜗功能。我们将使用实验2的结果来计算HI听者经历的调整后的有效可听度，同时考虑到HI听者经历的耳蜗增益的损失。在第三节中，我们将基于从相同听众那里获得的语音识别和心理声学测试结果来模拟和模拟耳蜗性听力损失的影响。我们假设，这些模型和模拟将提供准确和有用的预测MR在年轻的HI听众。我们将使用所得到的模型和模拟作为评估降噪信号处理的经验基础上的第一步。在以后的几年里，这些模型还可以进一步应用于严重听力损失的听众，以及患有听力损失的老年听众。总体而言，这些发现将有助于我们理解听力损失的本质，听力降低和耳蜗增益降低的影响，以及在各种噪声背景下理解语音的含义。我们假设，提高我们对减少掩蔽释放的本质的理解将提高我们开发信号处理算法的能力，这些算法可以更有效地补救HI听众在噪声中的困难。建议的实验和模型的公共卫生相关性结果将有助于理解听力受损的听众在背景噪声中理解语音的困难。我们预计，本项目中开发的模型将为评估信号处理算法奠定基础，以最大限度地提高噪声中的语音清晰度。

DESCRIPTION (provided by applicant): Listeners with sensorineural hearing loss experience significantly more masking and significantly less release from masking than do listeners with normal hearing sensitivity. When background noise is intermittent, normal- hearing (NH) listeners take advantage of the momentary dips in the noise to understand the target signal. This benefit is termed masking release (MR). Hearing-impaired (HI) listeners do not experience the same degree of MR as NH listeners. As a result, HI listeners cannot understand speech in noisy environments at the same signal-to-noise ratios in which NH listeners can understand successfully. At the same time, listeners with hearing loss frequently complain that their amplification devices are not satisfactory in background noise. We propose to further our understanding of the masking and MR experienced by listeners with hearing loss and to investigate the causes and potential sources of remediation. In Experiment 1 we will test MR in speech recognition experiments across a wide range of noise and signal levels and bandwidths. We will test NH and HI listeners, as well as NH listeners whose thresholds will be elevated by noise to match those of the HI listeners. We will measure listeners' sentence recognition in quiet, steady noise, and fluctuating noise and will define MR as the performance difference between steady and fluctuating noise. We hypothesize based on preliminary results that signal audibility will not fully explain the reduced MR of HI listeners, and that additional variability is explained by HI listeners' reduced access to spectrotemporal information about the speech in the dips of noise. We further hypothesize that underlying changes in cochlear physiology can explain HI listeners' difficulty in conditions of intermittent noise, and we propose to measure cochlear function in Experiment 2. We will measure basilar membrane input/output responses, masking period patterns, modulation masking, and frequency selectivity to describe HI listeners' cochlear function. We will use results from Experiment 2 to compute the adjusted effective audibility experienced by HI listeners taking into account the loss of cochlear gain experienced by HI listeners. In Section 3 we will model and simulate the effects of cochlear hearing loss based on speech recognition and psychoacoustic test results obtained from the same listeners. We hypothesize that these models and simulations will provide accurate and useful predictions of MR in young HI listeners. We will use the resulting models and simulations as empirically based first steps in evaluating signal processing for noise reduction. In later years the models can also be applied further to listeners with severe hearing loss, and to elderly listeners with hearing loss. Overall, the findings will contribute to our understanding of the nature of hearing loss, the effects of reduced audibility and cochlear gain, and the implications for understanding speech in a variety of noise backgrounds. We hypothesize that improving our understanding of the nature of reduced masking release will improve our ability to develop signal processing algorithms that can more effectively remediate HI listeners' difficulties in noise. PUBLIC HEALTH RELEVANCE Results from the proposed experiments and models will help understand hearing-impaired listeners' difficulty understanding speech in background noise. We anticipate that models developed in this project will lay the groundwork for evaluating signal-processing algorithms to maximize speech intelligibility in noise.