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Int J Audiol. 2018 Aug;57(8):561-569. doi: 10.1080/14992027.2018.1463465. Epub 2018 Apr 20.

Modernising speech audiometry: using a smartphone application to test word recognition.

Author information

1
a Department of Speech-Language Pathology and Audiology , University of Pretoria , Pretoria , South Africa.
2
b Callier Center for Communication Disorders , University of Texas , Dallas , TX , USA.
3
c Ear Sciences Centre, School of Surgery , University of Western Australia , Nedlands , Australia.
4
d Ear Science Institute Australia , Subiaco , Australia.
5
e Department of Electrical, Electronic and Computer Engineering , University of Pretoria , Pretoria , South Africa.

Abstract

OBJECTIVE:

This study aimed to develop and assess a method to measure word recognition abilities using a smartphone application (App) connected to an audiometer.

DESIGN:

Word lists were recorded in South African English and Afrikaans. Analyses were conducted to determine the effect of hardware used for presentation (computer, compact-disc player, or smartphone) on the frequency content of recordings. An Android App was developed to enable presentation of recorded materials via a smartphone connected to the auxiliary input of the audiometer. Experiments were performed to test feasibility and validity of the developed App and recordings.

STUDY SAMPLE:

Participants were 100 young adults (18-30 years) with pure tone thresholds ≤15 dB across the frequency spectrum (250-8000 Hz).

RESULTS:

Hardware used for presentation had no significant effect on the frequency content of recordings. Listening experiments indicated good inter-list reliability for recordings in both languages, with no significant differences between scores on different lists at each of the tested intensities. Performance-intensity functions had slopes of 4.05%/dB for English and 4.75%/dB for Afrikaans lists at the 50% point.

CONCLUSIONS:

The developed smartphone App constitutes a feasible and valid method for measuring word recognition scores, and can support standardisation and accessibility of recorded speech audiometry.

KEYWORDS:

Speech perception; mobile health; speech audiometry; tele-audiology; word recognition

PMID:
29676598
DOI:
10.1080/14992027.2018.1463465
[Indexed for MEDLINE]

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