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Title
Examining the Equivalence of Traditional vs. Automated Speech Perception Testing in Adult Listeners with Normal Hearing
Description
The purpose of the present study was to determine if an automated speech perception task yields results that are equivalent to a word recognition test used in audiometric evaluations. This was done by testing 51 normally hearing adults using a traditional word recognition task (NU-6) and an automated Non-Word Detection task. Stimuli for each task were presented in quiet as well as in six signal-to-noise ratios (SNRs) increasing in 3 dB increments (+0 dB, +3 dB, +6 dB, +9 dB, + 12 dB, +15 dB). A two one-sided test procedure (TOST) was used to determine equivalency of the two tests. This approach required the performance for both tasks to be arcsine transformed and converted to z-scores in order to calculate the difference in scores across listening conditions. These values were then compared to a predetermined criterion to establish if equivalency exists. It was expected that the TOST procedure would reveal equivalency between the traditional word recognition task and the automated Non-Word Detection Task. The results confirmed that the two tasks differed by no more than 2 test items in any of the listening conditions. Overall, the results indicate that the automated Non-Word Detection task could be used in addition to, or in place of, traditional word recognition tests. In addition, the features of an automated test such as the Non-Word Detection task offer additional benefits including rapid administration, accurate scoring, and supplemental performance data (e.g., error analyses) beyond those obtained in traditional speech perception measures.
Date Created
2017-05
Contributors
- Stahl, Amy Nicole (Author)
- Pittman, Andrea (Thesis director)
- Boothroyd, Arthur (Committee member)
- McBride, Ingrid (Committee member)
- School of Human Evolution and Social Change (Contributor)
- Department of Speech and Hearing Science (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
31 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2016-2017
Handle
https://hdl.handle.net/2286/R.I.43258
Level of coding
minimal
Cataloging Standards
System Created
- 2017-10-30 02:50:58
System Modified
- 2021-08-11 04:09:57
- 3 years 3 months ago
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