Online speech processing in pediatric and adult cochlear implant users

儿童和成人人工耳蜗用户的在线语音处理

• 批准号: 8254958
• 负责人: Ashley Wilson Farris-Trimble
• 金额: $ 5.3万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8254958
• 关键词: Accounting; Acoustic Nerve; Acoustics; Address; Adult; Affect; American; Auditory; Auricular prosthesis; Basic Science; Categories; Cellular Phone; Characteristics; Child; Childhood; Clinical; Cochlea; Cochlear Implants; Cognition; Computers; Cues; Data; Devices; Diagnostic; Electrodes; Exhibits; Eye; Eye Movements; Frequencies; Goals; Hearing; Hearing Impaired Persons; Implant; Implanted Electrodes; Incidence; Individual; Individual Differences; Language; Lead; Measures; Methodology; Modeling; Monitor; Nature; Neurons; Outcome; Outcome Measure; Output; Perception; Performance; Phonetics; Population; Problem Solving; Process; Process Measure; Prosthesis; Research; Research Personnel; Resolution; Sensory; Signal Transduction; Simulate; Sorting - Cell Movement; Speech; Speech Perception; Stimulus; Structure; System; Time; United States; Variant; Vision; Visual; Work; auditory stimulus; base; cognitive system; coping; deafness; improved; lexical; lexical processing; response; sound; speech processing; success; therapy development

DESCRIPTION (provided by applicant): It is estimated that 3 out of every 1000 people in the United States are deaf, and 60,000 Americans have cochlear implants, prosthetic devices that electrically stimulate the auditory nerve to simulate hearing. Previous research has shown that CI users exhibit a wide range of variability in word recognition and outcome measures of speech perception. Some work has focused on CI users' auditory deficits, but with recent advances in our understanding of the online processing necessary to speech perception and word recognition, we ask whether CI users' online processing abilities contribute to their differences in these tasks. The proposed research seeks to examine speech processing in the face of a degraded signal, and to determine how listeners adapt to that signal. Our goal is to characterize the nature of online processing and adaptation in this population, with three specific aims: to determine the factors that account for differences in lexical dynamics; to examine phonetic category structure and response to degradation in CI users via lexical activation; and to examine the nature and duration of competitor activation and in CI users. These aims will help us understand how CI users adapt to degraded signals and how sounds and words compete for activation in the lexicon. To measure online processing and lexical activation, we need a real-time measure of lexical activation, including that of the stimulus word and its competitors. We will use eye tracking in the visual world paradigm to measure this. As the listener does a basic word identification task on a computer, his or her eye movements are monitored as a measure of how strongly the listener is considering different words as a match to the auditory stimulus at that time. This yields a real-time measure of which competitors are being considered throughout processing. The task is straightforward and requires no metalinguistic interference, and as a result can be easily used with impaired populations like children and adult CI users. The proposed research has both clinical and theoretical implications. Clinically, we hope that by understanding specific ways in which CI users' online processing differs from that of normal hearers, and the ways in which CI users differ from one another in adaptation strategies, we can inform diagnostic criteria and provide data that will improve the processing strategies of the implants themselves. From a theoretical perspective, no model of speech perception has attempted to account for how degraded speech is perceived, and our preliminary results challenge some of the most basic principles of word recognition. The processing of degraded speech has broad implications: every time we hear speech in a noisy room, or talk on a cell phone, we are processing speech that has been degraded in some way. Understanding and modeling this process may thus inform researchers' strategies in coping with degraded speech. This set of studies will thus expanding our account of the cognitive system as a whole. PUBLIC HEALTH RELEVANCE: The research proposed here has direct relevance to a clinical population: deaf individuals, specifically those with a prosthetic cochlear implant (CI). The incidence of deafness in the US is around 3 cases per 1000 individuals, and there are approximately 60,000 cochlear implant users; the proposed studies attempt to account for the wide variation in outcome measures for this population by examining how CI users process speech and recognize words in real-time. The results are expected to inform diagnostic criteria for this population; moreover, they will enhance our understanding of the processing of a degraded signal in general, which affects many situations confronted by normal hearers on a daily basis, like hearing speech in a noisy room or talking on a cell phone.

描述（由申请人提供）：据估计，美国每 1000 人中就有 3 人耳聋，并且有 60,000 名美国人植入了人工耳蜗，这是一种通过电刺激听觉神经来模拟听力的假肢装置。先前的研究表明，CI 用户在单词识别和语音感知结果测量方面表现出广泛的变异性。一些工作集中在 CI 用户的听觉缺陷上，但随着我们对语音感知和单词识别所需的在线处理的理解的最新进展，我们询问 CI 用户的在线处理能力是否导致了他们在这些任务中的差异。拟议的研究旨在检查面对降级信号时的语音处理，并确定听众如何适应该信号。我们的目标是描述该人群在线处理和适应的本质，具有三个具体目标：确定导致词汇动态差异的因素；通过词汇激活检查语音类别结构和 CI 用户对退化的反应；并检查竞争对手和 CI 用户激活的性质和持续时间。这些目标将帮助我们了解 CI 用户如何适应退化的信号，以及声音和单词如何在词典中竞争激活。 为了测量在线处理和词汇激活，我们需要实时测量词汇激活，包括刺激词及其竞争对手的词汇激活。我们将使用视觉世界范例中的眼动追踪来衡量这一点。当听者在计算机上执行基本的单词识别任务时，他或她的眼球运动会受到监控，以衡量听者将不同单词与当时的听觉刺激相匹配的强烈程度。这样可以实时衡量在整个处理过程中正在考虑哪些竞争对手。该任务很简单，不需要元语言干扰，因此可以轻松地用于儿童和成人 CI 用户等受损人群。 拟议的研究具有临床和理论意义。在临床上，我们希望通过了解 CI 用户在线处理与正常听者不同的具体方式，以及 CI 用户在适应策略上的不同方式，我们可以告知诊断标准并提供数据，以改善听力损失。植入物本身的处理策略。从理论角度来看，没有任何语音感知模型试图解释退化的语音是如何被感知的，我们的初步结果挑战了单词识别的一些最基本的原则。退化语音的处理具有广泛的影响：每次我们在嘈杂的房间里听到语音或用手机通话时，我们都在处理以某种方式退化的语音。因此，理解和建模这一过程可以为研究人员应对言语退化的策略提供信息。因此，这组研究将扩展我们对整个认知系统的解释。 公共健康相关性：此处提出的研究与临床人群直接相关：聋哑人，特别是那些植入人工耳蜗 (CI) 的人。美国的耳聋发病率约为每 1000 人 3 例，大约有 60,000 名人工耳蜗使用者；拟议的研究试图通过检查 CI 用户如何实时处理语音和识别单词来解释该人群结果测量的巨大差异。预计结果将为该人群的诊断标准提供信息；此外，它们将增强我们对降级信号处理的理解，降级信号会影响正常听众每天遇到的许多情况，例如在嘈杂的房间里听到讲话或用手机通话。