Investigating the mechanisms of poor accent adaptation in healthy older adults

研究健康老年人口音适应不良的机制

• 批准号: 10315384
• 负责人: David Saltzman
• 金额: $ 4.6万
• 依托单位: UNIVERSITY OF CONNECTICUT STORRS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10315384
• 关键词: Accent; Adult; Affect; Age; Aging; Behavioral; Behavioral Model; Behavioral Paradigm; Characteristics; Cognitive; Competence; Comprehension; Computer Models; Data; Elderly; Evidence based intervention; Exposure to; Face; Failure; Fellowship; Foundations; Future; Gender; Health Professional; Hearing; Impaired cognition; Impairment; Intention; Intervention; Knowledge; Learning; Methods; Modeling; Modification; National Institute on Aging; Noise; Output; Patients; Perceptual learning; Performance; Plant Roots; Population; Presbycusis; Process; Proxy; Research; Research Personnel; Sensory; Series; Signal Transduction; Source; Specific qualifier value; Speech; Speech Perception; Speech Sound; Stimulus; Suggestion; Testing; To specify; Training; Weight; adjudicate; age group; age related; base; career; cognitive function; computer framework; design; efficacious intervention; expectation; experience; experimental study; hearing impairment; heuristics; human data; improved; insight; lexical; novel; processing speed; programs; remediation; sex; social; speech in noise; stem; theories; training opportunity; young adult

ABSTRACT Unfamiliar accented speech poses a significant barrier comprehension in older adults, and there is insufficient evidence to attribute it simply to age-related declines in hearing acuity or cognitive functioning. As the population of adults 65 and older in the US has grown dramatically in recent years, it is critical that interventions be developed to improve accent adaptation, but no such thing yet exists. In this proposal, we examine the hypothesis that generalization lays at the root of older adults’ issues with accent adaptation; specifically, older adults may be able to adapt to an accented talker with sufficient exposure, but fail to properly apply this information to future encounters with talkers who share the same accent. This perspective is informed by the Ideal Adapter model, a computational framework for speech perception wherein it is proposed that listeners independently track the way the speech signal is altered by different qualities of the talker, like age, sex, or accent, and use that information when adapting to an unfamiliar talker. Over the course of several behavioral experiments, we will compare younger and older adults’ generalization of accent information across talkers. In Experiments 1A & 1B, younger (18-22 years) and older adults (65+ years) will engage in lexically- guided perceptual learning (LGPL) task, a well-established, accent adaptation paradigm that we will modify to make more suitable for assessing generalization, such as adding a carrier sentence to each stimulus to provide the listener with more exposure to the accent. Performance between the two age groups will be compared, with the expectation that older adults will fail to generalize phonetic information to a novel talker of the same accent. In Experiment 2, older adults will listen to a story spoken with an artificial accent which better reflects naturalistic listening conditions, which both adds cognitive demands but also allows for the use of more top-down heuristics. The magnitude of generalization in older adults on the LGPL task in Experiment 1B and the story-listening task in Experiment 2 will then be compared. In Experiment 3, we will use the Ideal Adapter model to attempt to specify the mechanism that leads to impaired generalization in older adults. We will create several perturbations to the model that serve as proxies for age-related sensory/cognitive impairments like hearing loss or slower processing speed, as well as more conceptual impairments like the downweighing of previous experience. Output from the model will then be compared to older adults’ performance to adjudicate which perturbation best reflects human data. This proposal will yield novel insight into the mechanisms of accent adaptation in older adults, which in turn can be used by clinicians to better tailor interventions in the future. In addition, it will provide the applicant with training opportunities in (1) expanding my research into healthy older adults, (2) integrating computational modeling into my research program, and (3) networking with interdisciplinary researchers of aging, with the intention of utilizing these to establish a research program as the applicant moves towards independence in career as a researcher.

摘要 不熟悉的口音的讲话构成了一个显着的障碍理解老年人， 证据表明，这仅仅是由于年龄相关的听力敏锐度或认知功能下降。为 近年来，美国65岁及以上的成年人口急剧增长，至关重要的是， 干预措施，以改善口音适应，但还没有这样的事情存在。在本提案中，我们 检验假设，即泛化是老年人口音适应问题的根源; 具体来说，老年人可能能够适应一个有口音的谈话者，但不能正确地 将这些信息应用于将来遇到具有相同口音的谈话者。这种观点是 由理想适配器模型通知，语音感知的计算框架，其中提出 听众独立地跟踪语音信号被说话者的不同品质改变的方式， 年龄、性别或口音，并在适应不熟悉的谈话者时使用这些信息。在几 行为实验，我们将比较年轻人和老年人的口音信息的概括， 健谈的人在实验1A和1B中，年轻人（18 - 22岁）和老年人（65岁以上）将从事词汇- 引导知觉学习（LGPL）任务，一个完善的，口音适应范式，我们将修改， 使其更适合评估概括，例如为每个刺激添加载体句子， 让听者更容易听到口音两个年龄组之间的表现将是 相比之下，预期老年人将无法将语音信息概括为一个新的谈话者， 同样的口音。在实验2中，老年人会听一个带有人工口音的故事， 反映了自然主义的听力条件，既增加了认知需求，也允许使用更多的 自上而下的电子学在实验1B中，老年人在LGPL任务上的泛化程度， 然后将实验2中的听故事任务进行比较。在实验3中，我们将使用理想适配器 该模型试图详细说明导致老年人泛化能力受损的机制。我们将创建 模型的几个扰动，作为年龄相关的感觉/认知障碍的代理，如 听力损失或较慢的处理速度，以及更多的概念障碍，如 以前的经验。然后将模型的输出与老年人的表现进行比较， 该扰动最好地反映了人类数据。这一建议将产生新的见解的机制， 老年人的口音适应，这反过来又可以被临床医生用来更好地定制干预措施， 未来此外，它将为申请人提供培训机会（1）将我的研究扩展到 健康的老年人，（2）将计算建模融入我的研究计划，（3）与 老龄化的跨学科研究人员，利用这些建立一个研究计划， 申请人作为研究人员在职业生涯中走向独立。