How Does Inattention Influence the Robustness and Efficiency of Adaptive Procedures in the Context of Psychoacoustic Assessments via Smartphone?

IF 2.6 2区 医学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Chen Xu, David Hülsmeier, Mareike Buhl, Birger Kollmeier
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Abstract

Inattention plays a critical role in the accuracy of threshold measurements, e.g., when using mobile devices. To describe the influence of distraction, long- and short-term inattention models based on either a stationary or a non-stationary psychometric function were developed and used to generate three simulated listeners: fully-, moderately-, and non-concentrated listeners. Six established adaptive procedures were assessed via Monte-Carlo simulations in combination with the inattention models and compared with a newly proposed method: the graded response bracketing procedure (GRaBr). Robustness was examined by bias and root mean square error between the "true" and estimated thresholds while efficiency was evaluated using rates of convergence and a normalized efficiency index. The findings show that inattention has a detrimental impact on adaptive procedure performance-especially for the short-term inattentive listener-and that several model-based procedures relying on a consistent response behavior of the listener are prone to errors owing to inattention. The model-free procedure GRaBr, on the other hand, is considerably robust and efficient in spite of the (assumed) inattention. As a result, adaptive techniques with desired properties (i.e., high robustness and efficiency) as revealed in our simulations-such as GRaBr-appear to be advantageous for mobile devices or in laboratory tests with untrained subjects.

在通过智能手机进行心理声学评估时,注意力不集中如何影响自适应程序的稳健性和效率?
注意力不集中对阈值测量的准确性起着至关重要的作用,例如在使用移动设备时。为了描述注意力分散的影响,我们开发了基于静态或非静态心理测量函数的长期和短期注意力不集中模型,并将其用于生成三种模拟听者:完全集中、中度集中和非集中听者。通过蒙特卡洛模拟,结合注意力不集中模型,对六种已建立的自适应程序进行了评估,并与一种新提出的方法进行了比较:分级反应括弧程序(GRaBr)。稳健性通过 "真实 "阈值和估计阈值之间的偏差和均方根误差进行检验,而效率则通过收敛率和归一化效率指数进行评估。研究结果表明,注意力不集中会对自适应程序的性能产生不利影响--尤其是对短期注意力不集中的听者而言,而且一些基于模型的程序依赖于听者一致的反应行为,容易因注意力不集中而出错。另一方面,尽管存在(假定的)注意力不集中的情况,无模型程序 GRaBr 仍具有相当高的稳健性和效率。因此,我们的模拟结果表明,具有理想特性(即高鲁棒性和高效性)的自适应技术(如 GRaBr)在移动设备或未经训练的受试者的实验室测试中似乎更具优势。
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来源期刊
Trends in Hearing
Trends in Hearing AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGYOTORH-OTORHINOLARYNGOLOGY
CiteScore
4.50
自引率
11.10%
发文量
44
审稿时长
12 weeks
期刊介绍: Trends in Hearing is an open access journal completely dedicated to publishing original research and reviews focusing on human hearing, hearing loss, hearing aids, auditory implants, and aural rehabilitation. Under its former name, Trends in Amplification, the journal established itself as a forum for concise explorations of all areas of translational hearing research by leaders in the field. Trends in Hearing has now expanded its focus to include original research articles, with the goal of becoming the premier venue for research related to human hearing and hearing loss.
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