Perception of Dynamic Acoustic Signals by Hearing Impaired Listeners

描述(申请人提供)：语音是一种固有的动态信号，频谱动态对辅音和元音的感知都是不可或缺的。共振峰移动的速度、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敏感度、精确的时间处理和频率选择性的丧失将扰乱共振峰运动的感知。因此，动态光谱提示的减少或消除可能会损害语音理解，特别是在诸如背景噪声或混响等不利的听力条件下。这项研究的目的是了解听力受损的人对动态声音信号的感知，长期目标是提高这些人的言语理解能力，特别是在恶劣的听力条件下。这项拟议的研究比较了听力正常和听力受损的听者在一系列任务中的表现，这些任务旨在评估对复杂的非语音听觉刺激的基本感知能力，这些刺激的频率会随着时间的推移而变化。实验程序将包括对具有语音时间和频率特性的非语音刺激进行光谱变化检测和识别的自适应测试，以及在几种类型的竞争背景噪声和模拟混响中估计光谱变化检测和识别阈值。在背景噪音和混响中的语音识别能力也将被评估。基于这些光谱变化感知和语音识别行为测量的结果，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的差异。计算模型的有效性将通过将模型预测与实际听众表现进行比较来评估。将有关光谱变化感知的信息应用于语音识别模型将对开发新的助听器处理策略和康复听觉训练计划具有指导意义，这些策略和计划可能提高语言可理解性并减少听力受损个体的听力努力。

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.