Effects of Age and Uncertainty on the Visual Speech Benefit in Noise

Author:

Beadle Julie12,Kim Jeesun1,Davis Chris12ORCID

Affiliation:

1. The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, New South Wales, Australia

2. The HEARing Cooperative Research Centre, Carlton, Victoria, Australia

Abstract

Purpose: Listeners understand significantly more speech in noise when the talker's face can be seen (visual speech) in comparison to an auditory-only baseline (a visual speech benefit). This study investigated whether the visual speech benefit is reduced when the correspondence between auditory and visual speech is uncertain and whether any reduction is affected by listener age (older vs. younger) and how severe the auditory signal is masked. Method: Older and younger adults completed a speech recognition in noise task that included an auditory-only condition and four auditory–visual (AV) conditions in which one, two, four, or six silent talking face videos were presented. One face always matched the auditory signal; the other face(s) did not. Auditory speech was presented in noise at −6 and −1 dB signal-to-noise ratio (SNR). Results: When the SNR was −6 dB, for both age groups, the standard-sized visual speech benefit reduced as more talking faces were presented. When the SNR was −1 dB, younger adults received the standard-sized visual speech benefit even when two talking faces were presented, whereas older adults did not. Conclusions: The size of the visual speech benefit obtained by older adults was always smaller when AV correspondence was uncertain; this was not the case for younger adults. Difficulty establishing AV correspondence may be a factor that limits older adults' speech recognition in noisy AV environments. Supplemental Material https://doi.org/10.23641/asha.16879549

Publisher

American Speech Language Hearing Association

Subject

Speech and Hearing,Linguistics and Language,Language and Linguistics

Reference39 articles.

1. Searching for audiovisual correspondence in multiple speaker scenarios

2. Aubanel V. Davis C. & Kim J. (2017). The MAVA corpus. https://app.alveo.edu.au/catalog/mava

3. The Freiburg Visual Acuity Test-Variability unchanged by post-hoc re-analysis

4. Bates D. Kliegl R. Vasishth S. & Baayen H. (2015). Parsimonious mixed models. arXiv: 1506.04967.

5. Champely S. Ekstrom C. Dalgaard P. Gill J. Weibelzahl S. Anandkumar A. Ford C. Volcic R. & De Rosario M. H. (2018). Package “pwr” (R package Version 1.3-0) . https://cran.r-project.org/web/packages/pwr/pwr.pdf

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3