Title |
International Collegium of Rehabilitative Audiology (ICRA) recommendations for the construction of multilingual speech tests
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Published in |
International Journal of Audiology, April 2015
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DOI | 10.3109/14992027.2015.1030513 |
Pubmed ID | |
Authors |
Michael A. Akeroyd, Stig Arlinger, Ruth A. Bentler, Arthur Boothroyd, Norbert Dillier, Wouter A. Dreschler, Jean-Pierre Gagné, Mark Lutman, Jan Wouters, Lena Wong, Birger Kollmeier |
Abstract |
To provide guidelines for the development of two types of closed-set speech-perception tests that can be applied and interpreted in the same way across languages. The guidelines cover the digit triplet and the matrix sentence tests that are most commonly used to test speech recognition in noise. They were developed by a working group on Multilingual Speech Tests of the International Collegium of Rehabilitative Audiology (ICRA). The recommendations are based on reviews of existing evaluations of the digit triplet and matrix tests as well as on the research experience of members of the ICRA Working Group. They represent the results of a consensus process. The resulting recommendations deal with: Test design and word selection; Talker characteristics; Audio recording and stimulus preparation; Masking noise; Test administration; and Test validation. By following these guidelines for the development of any new test of this kind, clinicians and researchers working in any language will be able to perform tests whose results can be compared and combined in cross-language studies. |
X Demographics
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Unknown | 1 | 100% |
Demographic breakdown
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 120 | 100% |
Demographic breakdown
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Researcher | 20 | 17% |
Student > Ph. D. Student | 18 | 15% |
Student > Master | 14 | 12% |
Student > Bachelor | 13 | 11% |
Professor | 7 | 6% |
Other | 14 | 12% |
Unknown | 34 | 28% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 22 | 18% |
Nursing and Health Professions | 13 | 11% |
Psychology | 9 | 8% |
Engineering | 9 | 8% |
Neuroscience | 8 | 7% |
Other | 17 | 14% |
Unknown | 42 | 35% |