Subjective Speech Intelligibility Drives Noise-Tolerance Domain Use During the Tracking of Noise-Tolerance Test.

IF 2.6 2区 医学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY Ear and Hearing Pub Date : 2024-11-01 Epub Date: 2024-06-17 DOI:10.1097/AUD.0000000000001536
Francis Kuk, Christopher Slugocki, Petri Korhonen
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Abstract

Objectives: Recently, the Noise-Tolerance Domains Test (NTDT) was applied to study the noise-tolerance domains used by young normal-hearing (NH) listeners during noise acceptance decisions. In this study, we examined how subjective speech intelligibility may drive noise acceptance decisions by applying the NTDT on NH and hearing-impaired (HI) listeners at the signal to noise ratios (SNRs) around the Tracking of Noise-Tolerance (TNT) thresholds.

Design: A single-blind, within-subjects design with 22 NH and 17 HI older adults was followed. Listeners completed the TNT to determine the average noise acceptance threshold (TNT Ave ). Then, listeners completed the NTDT at the SNRs of 0, ±3 dB (re: TNT Ave ) to estimate the weighted noise-tolerance domain ratings (WNTDRs) for each domain criterion. Listeners also completed the Objective and Subjective Intelligibility Difference (OSID) Test to establish the individual intelligibility performance-intensity (P-I) functions of the TNT materials. All test measures were conducted at 75 and 82 dB SPL speech input levels. NH and HI listeners were tested in the unaided mode. The HI listeners were also tested using a study hearing aid. The WNTDRs were plotted against subjective speech intelligibilities extrapolated from individual P-I of the OSID at the SNRs corresponding to NTDT test conditions. Listeners were grouped according to their most heavily weighed domain and a regression analysis was performed against listener demographics as well as TNT and OSID performances to determine which variable(s) affected listener grouping.

Results: Three linear mixed effects (LMEs) models were used to examine whether WNTDRs changed with subjective speech intelligibility. All three LMEs found significant fixed effects of domain criteria, subjective intelligibility, and speech input level on WNTDRs. In general, heavier weights were assigned to speech interference and loudness domains at poorer intelligibility levels (<50%) with reversals to distraction and annoyance at higher intelligibility levels (>80%). The comparison between NH and HI-unaided showed that NH listeners assigned greater weights to loudness than the HI-unaided listeners. The comparison between NH and HI-aided groups showed similar weights between groups. The comparison between HI-unaided and HI-aided found that HI listeners assigned lower weights to speech interference and greater weights to loudness when tested in aided compared with unaided modes. In all comparisons, loudness was weighed heavier at the 82 dB SPL input level than at the 75 dB SPL input level with greater weights to annoyance in the NH versus HI-unaided comparison and lower weights to distraction in the HI-aided versus HI-unaided comparison. A generalized linear model determined that listener grouping was best accounted for by subjective speech intelligibility estimated at TNT Ave .

Conclusions: The domain criteria used by listeners were driven by their subjective speech intelligibility regardless of their hearing status (i.e., NH versus HI). In general, when subjective intelligibility was poor, the domains of speech interference and loudness were weighed the heaviest. As subjective intelligibility improved, the weightings on annoyance and distraction increased. Furthermore, a listener's criterion for >90% subjective speech understanding at the TNT Ave may allow one to profile the listener.

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在噪声耐受性跟踪测试中,主观语音清晰度驱动噪声耐受性域的使用。
研究目的最近,噪声耐受域测试(NTDT)被用于研究年轻的正常听力(NH)听者在决定是否接受噪声时所使用的噪声耐受域。在本研究中,我们通过对听力正常(NH)和听力受损(HI)的听者在噪声容限跟踪(TNT)阈值附近的信噪比(SNR)进行NTDT测试,研究了主观语音清晰度如何驱动噪声接受决策:设计:对 22 名 NH 和 17 名 HI 老年人进行单盲、受试者内设计。听者完成 TNT 测试以确定平均噪声接受阈值 (TNTAve)。然后,听者在信噪比为 0、±3 dB(重 TNTAve)时完成 NTDT,以估算每个领域标准的加权噪声耐受领域评级(WNTDRs)。听者还完成了客观和主观智能度差异(OSID)测试,以确定 TNT 材料的个人智能度性能-强度(P-I)函数。所有测试均在 75 和 82 dB SPL 的语音输入水平下进行。NH 和 HI 听者在无辅助模式下进行测试。HI 听力者还使用助听器进行了测试。在与 NTDT 测试条件相对应的信噪比下,将 WNTDR 与 OSID 的单个 P-I 推断出的主观言语智能度进行对比。根据听者最重的权重域对其进行分组,并针对听者人口统计学特征以及 TNT 和 OSID 的表现进行回归分析,以确定哪些变量会影响听者分组:我们使用了三个线性混合效应(LMEs)模型来研究 WNTDRs 是否会随着主观语音清晰度的变化而变化。所有三个线性混合效应模型都发现了领域标准、主观清晰度和语音输入水平对 WNTDRs 的显著固定效应。一般来说,在较差的清晰度水平(80%)下,语音干扰和响度域的权重较高。国家听力和人工智能无辅助听力之间的比较表明,国家听力听者比人工智能无辅助听者对响度赋予了更大的权重。NH 和 HI 辅助听力组之间的比较显示,各组之间的权重相似。在无辅助听力组和有辅助听力组之间的比较中发现,与无辅助听力模式相比,有辅助听力模式下的听力测试中,辅助听力组听者对语音干扰赋予的权重较低,而对响度赋予的权重较高。在所有比较中,82 dB SPL 输入水平时的响度权重高于 75 dB SPL 输入水平时的响度权重,在 NH 与 HI 无辅助比较中,烦扰权重较大,而在 HI 辅助与 HI 无辅助比较中,干扰权重较低。一个广义线性模型确定,听者分组的最佳解释是在 TNTAve 下估计的主观语音清晰度:无论听力状况如何(即 NH 与 HI),听者使用的领域标准都受其主观语音清晰度的影响。一般来说,当主观语言清晰度较低时,语言干扰和响度的权重最大。随着主观清晰度的提高,烦扰和分心的权重也随之增加。此外,听者在 TNTAve 下的主观语音理解度大于 90% 的标准可以帮助我们对听者进行特征分析。
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来源期刊
Ear and Hearing
Ear and Hearing 医学-耳鼻喉科学
CiteScore
5.90
自引率
10.80%
发文量
207
审稿时长
6-12 weeks
期刊介绍: From the basic science of hearing and balance disorders to auditory electrophysiology to amplification and the psychological factors of hearing loss, Ear and Hearing covers all aspects of auditory and vestibular disorders. This multidisciplinary journal consolidates the various factors that contribute to identification, remediation, and audiologic and vestibular rehabilitation. It is the one journal that serves the diverse interest of all members of this professional community -- otologists, audiologists, educators, and to those involved in the design, manufacture, and distribution of amplification systems. The original articles published in the journal focus on assessment, diagnosis, and management of auditory and vestibular disorders.
期刊最新文献
Associations Between Vestibular Perception and Cognitive Performance in Healthy Adults. Sounds of Nature and Hearing Loss: A Call to Action. Breathy Vocal Quality, Background Noise, and Hearing Loss: How Do These Adverse Conditions Affect Speech Perception by Older Adults? Effects of Tympanic Membrane Electrodes on Sound Transmission From the Ear Canal to the Middle and Inner Ears. The Optimal Speech-to-Background Ratio for Balancing Speech Recognition With Environmental Sound Recognition.
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