Literature DB >> 19951143

Sentence recognition in noise: Variables in compilation and interpretation of tests.

Marianne Theunissen1, De Wet Swanepoel, Johan Hanekom.   

Abstract

Tests of sentence recognition in noise constitute an essential tool for the assessment of auditory abilities that are representative of everyday listening experiences. A number of recent articles have reported on the development of such tests, documenting different approaches and methods. However, both the development and interpretation of these tests require careful consideration of many variables. This article reviews and categorizes the stimulus, presentation, subject, response, and performance variables influencing the development and interpretation of tests of sentence recognition in noise. A systematic framework is utilized to document published findings on these variables. Recommendations and guidelines, based on test performance requirements and test objectives, are provided concerning the interpretation of results and the development of new test materials.

Mesh:

Year:  2009        PMID: 19951143     DOI: 10.3109/14992020903082088

Source DB:  PubMed          Journal:  Int J Audiol        ISSN: 1499-2027            Impact factor:   2.117


  13 in total

1.  Development, reliability, and validity of PRESTO: a new high-variability sentence recognition test.

Authors:  Jaimie L Gilbert; Terrin N Tamati; David B Pisoni
Journal:  J Am Acad Audiol       Date:  2013-01       Impact factor: 1.664

2.  Effect of face masks on speech understanding: A clinical perspective during speech audiometry.

Authors:  Rawish Kumar; Sanjay Kumar Munjal; Anuradha Sharma; Md Noorain Alam; Naresh K Panda
Journal:  J Otol       Date:  2022-04-29

3.  Glimpsing keywords across sentences in noise: A microstructural analysis of acoustic, lexical, and listener factors.

Authors:  Daniel Fogerty; Jayne B Ahlstrom; Judy R Dubno
Journal:  J Acoust Soc Am       Date:  2021-09       Impact factor: 2.482

4.  Differential weighting of temporal envelope cues from the low-frequency region for Mandarin sentence recognition in noise.

Authors:  Yang Guo; Zhong Zheng; Keyi Li; Yuanyuan Sun; Liang Xia; Di Qian; Yanmei Feng
Journal:  BMC Neurosci       Date:  2022-06-13       Impact factor: 3.264

5.  Tracking Cognitive Spare Capacity During Speech Perception With EEG/ERP: Effects of Cognitive Load and Sentence Predictability.

Authors:  Cynthia R Hunter
Journal:  Ear Hear       Date:  2020 Sep/Oct       Impact factor: 3.570

6.  Adult Users of the Oticon Medical Neuro Cochlear Implant System Benefit from Beamforming in the High Frequencies.

Authors:  Bianca Bastos Cordeiro; Marcos Roberto Banhara; Carlos Maurício Cardeal Mendes; Fabiana Danieli; Ariane Laplante-Lévesque; Chadlia Karoui; Michel Hoen; Marine Ardoint; Fanny Gauvrit; Romane Demullier; Christophe Vincent
Journal:  Audiol Res       Date:  2021-04-16

7.  Evaluating a smartphone digits-in-noise test as part of the audiometric test battery.

Authors:  Jenni-Mari Potgieter; De Wet Swanepoel; Cas Smits
Journal:  S Afr J Commun Disord       Date:  2018-05-21

8.  First-language raters' opinions when validating word recordings for a newly developed speech reception threshold test.

Authors:  Seema Panday; Harsha Kathard; Mershen Pillay; Wayne Wilson
Journal:  S Afr J Commun Disord       Date:  2018-03-29

9.  The effect of background noise on speech perception in monolingual and bilingual adults with normal hearing.

Authors:  Danah Alqattan; Paul Turner
Journal:  Noise Health       Date:  2021 Jul-Sep       Impact factor: 0.867

10.  The internal and external consistency of a speech reception threshold test for isiZulu speakers with normal hearing sensitivity.

Authors:  Seema Panday; Harsha Kathard; Mershen Pillay; Wayne Wilson
Journal:  S Afr J Commun Disord       Date:  2018-06-25
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