Perception of Dynamic Acoustic Signals by Hearing Impaired Listeners

描述（由申请人提供）：语音是固有的动态信号，并且频谱动态对于辅音和元音的感知是不可或缺的。共振峰移动的速率、方向和程度为辅音和元音的同一性提供了线索。与听力损失和衰老相关的外周听觉灵敏度、精确时间处理和频率选择性的丧失将破坏共振峰运动的感知。因此，动态频谱线索的减少或消除可能会损害语音理解，特别是在不利的收听条件下，如背景噪声或混响。该研究计划的目的是了解听障听众对动态声学信号的感知，其长期目标是提高这些人的语音理解，特别是在不利的听力条件下。拟议的研究比较了听力正常和听力受损的听众在一些任务上的表现，这些任务旨在评估对频率随时间变化的复杂非语音听觉刺激的基本感知能力。实验程序将包括自适应测试的频谱变化检测和歧视，在非语音刺激，具有时间和频率特性的语音，和估计的频谱变化检测和歧视阈值在几种类型的竞争背景噪声和模拟混响。还将评估在背景噪声和混响中的语音识别能力。基于频谱变化感知和语音识别的这些行为测量的结果，将开发一个计算模型，该模型可以解释由于听力状态和刺激特征而导致的语音清晰度差异。计算模型的有效性将通过比较模型预测与实际听众的表现进行评估。有关频谱变化感知的语音识别模型的应用程序的信息将有影响的发展，新的助听器处理策略和康复听觉训练计划，可以提高语音清晰度，减少听力受损的个人听的努力。

DESCRIPTION (provided by applicant): Speech is an inherently dynamic signal and spectral dynamics are integral to perception of both consonants and vowels. The rate, direction, and extent of formant movements provide cues to consonant and vowel identity. The loss of peripheral auditory sensitivity, precise temporal processing, and frequency selectivity associated with hearing loss and aging will disrupt the perception of formant movements. As a result, the reduction or elimination of dynamic spectral cues may impair speech understanding, especially in adverse listening conditions such as background noise or reverberation. The purpose of this program of research is to understand the perception of dynamic acoustic signals by hearing-impaired listeners, with the long-term goal of improving speech understanding by these individuals, especially in adverse listening conditions. The proposed research compares the performance of normally-hearing and hearing-impaired listeners on a number of tasks designed to assess basic perceptual abilities in response to complex, non-speech auditory stimuli that change in frequency over time. Experimental procedures will consist of adaptive tests of spectral change detection and discrimination in non-speech stimuli which possess timing and frequency characteristics to those of speech, and estimation of spectral change detection and discrimination thresholds in several types of competing background noise and with simulated reverberation. Speech recognition ability in background noise and reverberation will also be assessed. Based on the results of these behavioral measures of spectral change perception and speech recognition, a computational model will be developed that can account for differences in speech intelligibility due to hearing status and stimulus characteristics. The effectiveness of the computational model will be evaluated by comparing model predictions with actual listener performance. The application of information regarding spectral change perception to a model of speech recognition will have implications for the development of new hearing aid processing strategies and rehabilitative auditory training programs that may enhance speech intelligibility and reduce listening effort in hearing-impaired individuals.