Individualized Assessment and Prediction of Speech-Recognition Performance In Adults with Age-related Hearing Loss

年龄相关性听力损失成人的语音识别表现的个体化评估和预测

• 批准号: 10456939
• 负责人: Yi Shen
• 金额: $ 29.96万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10456939
• 关键词: Acoustics; Address; Adopted; Adult; Age; Algorithms; Americas; Assessment tool; Auditory; Clinical; Cognitive; Cognitive deficits; Communities; Complex; Cues; Custom; Dependence; Diagnostic Procedure; Diagnostic tests; Elderly; Environment; Face; Frequencies; Future; Goals; Guidelines; Health Personnel; Healthcare; Hearing; Hearing Aids; Hour; Individual; Individual Differences; Laboratory Finding; Laboratory Research; Link; Lipreading; Measures; Methods; Modeling; Noise; Patients; Performance; Persons; Presbycusis; Procedures; Research; Role; Services; Short-Term Memory; Signal Transduction; Source; Speech; Speech Audiometry; Speech Intelligibility; Standard Model; Standardization; Testing; Time; Translating; Visual; Weight; base; clinical practice; cognitive skill; diagnostic tool; experience; hearing impairment; improved; indexing; individual patient; predictive modeling; programs; speech recognition; temporal measurement; tool

The main complaint from listeners with age-related hearing loss is the difficulty in understanding speech in noisy environments. The sources of the speech-understanding difficulty involve auditory and cognitive factors and vary from one listener to another. Developing models of speech intelligibility that can account for these factors is necessary for predicting expected speech-recognition performance with or without the use of a hearing aid. Moreover, if such models can be efficiently fitted to individual hearing-aid users, then the amplification profile in the hearing aid can be customized to the users' specific needs. However, such efficient diagnostic procedures for fitting models of speech-intelligibility are not yet available. The proposed research program will address this issue directly. The long-term goal of the program is to establish an efficient diagnostic test to enable individualized hearing-aid fitting. As a first step toward this goal, a Bayesian adaptive procedure for fitting a widely-adopted model of speech intelligibility, i.e. the Speech Intelligibility Index (ANSI S3.5-1997), to individual listeners will be examined in detail. The Bayesian adaptive procedure uses a speech recognition task, similar to clinical speech audiometry, and it allows the estimation of the model parameters for the Speech Intelligibility Index using as few as 75 test sentences (approximately 12 minutes of testing time). These estimated parameters indicate (1) how much acoustic cues in various frequency bands are being used for speech recognition, (2) the signal-to-noise ratio required to reach a performance level of 50% correct recognition, and (3) the listener's benefits from contextual cues in speech. The relationship between these model parameters to listener's auditory and cognitive skills will be systematically evaluated using a group of older adults with diverse age and hearing status. The parameters will also be studied under two common listening conditions: speech recognition in temporally fluctuating backgrounds, and speech recognition with visual cues (i.e. the display of the talker's face). The dependencies of the model parameters for these commonly occurring listening conditions will be investigated. Additionally, the estimated model using the Bayesian adaptive procedure will be used to predict speech-recognition performance under aided and unaided conditions. Whether the individualized Speech Intelligibility Index provides additional predictive power compared to the standard model will be evaluated. The estimated model will also be used to optimize the amplification profiles for individual hearing-impaired listeners, and its relationship to the listeners' preferred amplification profiles will be examined. Upon the completion of the proposed research program, a model will be established to provide comprehensive profiling of listeners' speech-recognition performance. Moreover, a set of tools will be made available to efficiently fit the model to individual listeners and to optimize the amplification profile according to the estimated model parameters.

与年龄有关的听力损失的听众的主要抱怨是难以理解英语中的讲话