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Comparison of Gated Audiovisual Speech Identification in Elderly Hearing Aid Users and Elderly Normal-Hearing Individuals

Overview of attention for article published in Trends in Hearing, June 2016
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Title
Comparison of Gated Audiovisual Speech Identification in Elderly Hearing Aid Users and Elderly Normal-Hearing Individuals
Published in
Trends in Hearing, June 2016
DOI 10.1177/2331216516653355
Pubmed ID
Authors

Shahram Moradi, Björn Lidestam, Jerker Rönnberg

Abstract

The present study compared elderly hearing aid (EHA) users (n = 20) with elderly normal-hearing (ENH) listeners (n = 20) in terms of isolation points (IPs, the shortest time required for correct identification of a speech stimulus) and accuracy of audiovisual gated speech stimuli (consonants, words, and final words in highly and less predictable sentences) presented in silence. In addition, we compared the IPs of audiovisual speech stimuli from the present study with auditory ones extracted from a previous study, to determine the impact of the addition of visual cues. Both participant groups achieved ceiling levels in terms of accuracy in the audiovisual identification of gated speech stimuli; however, the EHA group needed longer IPs for the audiovisual identification of consonants and words. The benefit of adding visual cues to auditory speech stimuli was more evident in the EHA group, as audiovisual presentation significantly shortened the IPs for consonants, words, and final words in less predictable sentences; in the ENH group, audiovisual presentation only shortened the IPs for consonants and words. In conclusion, although the audiovisual benefit was greater for EHA group, this group had inferior performance compared with the ENH group in terms of IPs when supportive semantic context was lacking. Consequently, EHA users needed the initial part of the audiovisual speech signal to be longer than did their counterparts with normal hearing to reach the same level of accuracy in the absence of a semantic context.

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Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 25%
Researcher 3 25%
Student > Bachelor 1 8%
Student > Master 1 8%
Unknown 4 33%
Readers by discipline Count As %
Psychology 4 33%
Linguistics 1 8%
Business, Management and Accounting 1 8%
Computer Science 1 8%
Engineering 1 8%
Other 0 0%
Unknown 4 33%