A multi-modal streaming approach to understanding aided speech perception in noise: discovering relationships between device limitations, perceptual abilities, and neuro-modulation of feature coding

一种理解噪声中辅助语音感知的多模态流方法：发现设备限制、感知能力和特征编码的神经调制之间的关系

基本信息

批准号：
10306355
负责人：
Erol James Ozmeral
金额：
$ 14.95万
依托单位：
UNIVERSITY OF SOUTH FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-12-01 至 2023-11-30
项目状态：
已结题

项目摘要

PROJECT SUMMARY/ABSTRACT It is estimated that only about 1 in 7 Americans who have hearing loss use some hearing assistive device despite the generally accepted view that devices such as hearing aids (HAs) improve hearing health and quality of life. Among the most common reasons for low adoption is an unclear benefit when trying to follow a conversation in the presence of noise. To address this problem, most premium HAs employ adaptive directional processing (DP) that reduces gain at locations considered less relevant, thus improving signal-to-noise ratios (SNRs) of more relevant speech. This strategy, however, is susceptible to processing delays and inaccurate speech localization, and though HA DP has assumed benefits, the neural mechanisms associated with it are not well understood. One would expect that HAs support acoustic-feature representation by increasing SNR; however, if a listener's speech localization is poor in noise and HA DP is delayed or inaccurate, poor perceptual- feature representation (e.g., space) may prevent effective auditory streaming. Past investigations have assessed DP benefits relative to unaided or omnidirectional amplification and have either assumed accurate adaptation or used a fixed directional focus. Moreover, benefit is typically gauged by self-report, listening effort, or sentence recognition in noise. This traditional approach has important limitations: 1) studies lack systematic control of HA DP because of manufacturer-placed barriers, and 2) results provide only indirect measures of the mechanisms responsible for the presumed advantages. In contrast, here we link controlled HA DP evaluation to a strong and established theoretical model of auditory object-based attention. In doing so, we can directly associate benefits of HA DP with relevant neural mechanisms, and we can more precisely target innovation efforts for future HA technology. Our multi-modal streaming approach incorporates 1) systematic control of HA DP, 2) an assay of basic perceptual abilities, and 3) measures of neural processing that support auditory streaming. In Aim 1, we parametrically vary the spatial and temporal precision of gain reduction during a novel speech-in-noise task, to assess directly the effects of focal and timelier transitions to speech location in the free field (Exp. 1). In Aim 2, we use our multi-modal streaming approach to measure the effect of hearing aids on spatial tuning curve sharpness both when passively listening (Exp. 2a) and when attending to a spatial location (Exp. 2b). Observed benefits in DP strategies are then analyzed with respect to psychophysical measures identified as potential predictors of HA DP (Aim 3). The results of this study will deliver a novel understanding of aided speech perception in noise and guide future HA development grounded in an established theory of auditory streaming. Planned R01 research will futher investigate aided acoustic and perceptual feature coding and auditory streaming in an auditory-object based model of attention.

项目摘要/摘要据估计，有听力损失的七分之一的美国人使用了一些听力辅助设备尽管人们普遍认为助听器（诸如助听器（已）改善听力健康和质量的设备生活。低采用率最常见的原因之一是尝试遵循在噪音的情况下对话。为了解决这个问题，大多数高级都采用了自适应方向加工（DP）可以减少被认为不相关的位置的增益，从而提高信号噪声比率（SNR）更相关的语音。但是，该策略容易处理延迟和不准确语音本地化，尽管HA DP已经取得了好处，但与之相关的神经机制不是理解。人们会期望通过增加SNR来支持声学代表。但是，如果听众的言语本地化在噪声方面较差，并且HA DP延迟或不准确，则感知性不佳 - 功能表示（例如，空间）可能会阻止有效的听觉流。过去的调查已经评估 DP相对于独立或全向扩增的好处，并假定适应或使用了固定的定向焦点。此外，通常会通过自我报告，听力努力或句子来衡量利益噪音的识别。这种传统方法具有重要的局限性：1）研究缺乏对HA的系统控制 DP由于制造商的屏障，2）结果仅提供间接衡量机制的措施负责假定的优势。相反，在这里我们将受控的HA DP评估链接到一个强大的和建立了基于听觉对象的注意的理论模型。这样，我们可以直接将福利联系在一起 HA DP具有相关的神经机制，我们可以更精确地针对未来HA的创新工作技术。我们的多模式流方法包括1）HA DP的系统控制，2）基本的感知能力和3）支持听觉流的神经处理的度量。在AIM 1中，我们参数用新颖的噪声任务期间的增益减少的空间和时间精度为直接评估焦点和及时过渡到自由场中语音位置的影响（exp。1）。在AIM 2中，我们使用多模式流方法来测量助听器对空间调谐曲线的影响当被动聆听时（经验2a）和参与空间位置（exp。2b）时，清晰度。观察到然后分析DP策略中的好处 HA DP的预测因素（AIM 3）。这项研究的结果将对辅助语音进行新的了解噪声和指导未来的HA发展的感知以既定的听觉流理论为基础。计划的R01研究将为辅助声学和感知功能编码和听觉调查在基于听觉对象的注意力模型中流式传输。