What can the pure-tone audiogram tell us about a patientʼs SNR loss?

Killion, Mead C.; Niquette, Patricia A.

doi:10.1097/00025572-200003000-00006

Cited by 119 publications

(84 citation statements)

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“…While there was no available classification of SNR loss, and to enable the results to be used more conveniently, according to pathology research data [34], Killion and Niquette [1] suggested that a loss of 20 dB in ability to understand speech in noise excluded the patient from social conversation at parties (profound loss), and initially suggested categories for SNR loss as: mild (0-4 dB), moderate (5-10 dB), severe (11-19 dB) and profound (20 dB). Then combined with Quick SIN test, the refining classification for SNR loss (normal ≤ 2 dB, mild 3-7 dB, moderate 7-15 dB and severe ≥ 15 dB) became accepted (Etymotic Research 2001).…”

Section: Discussionmentioning

confidence: 99%

“…But for hearingimpaired people even with hearing aids, understanding speech in background noise is one of their biggest challenges. Killion and Niquette's [1] physiologic research indicated that the loss of outer and inner hair cells causes a loss of sensitivity to quiet sounds as well as a loss of sound clarity. However, most sensorineural hearing loss patients' damage mainly due to loss of outer hair cells, so "can hear" and "can understand" became two independent concepts.…”

Section: Introductionmentioning

confidence: 99%

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Development and Evaluation of the Mandarin Quick Speech-in-Noise Test Materials in Mainland China

Zhou¹,

Hua²,

Wang³

et al. 2017

J Phonet and Audiol

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Objective: To develop and evaluate the Mandarin Quick Speech-in-Noise (M-Quick SIN) Test materials in mainland China.Design: Four parts were included in the experiment to (1) develop sentence materials and select equivalent sentences, (2) evaluate the reliability of the lists we grouped afterwards, (3) discuss the formula of SNR loss fitted for M-Quick SIN, and (4) quantify the classification of SNR loss among normal-hearing and hearing-impaired people. 132 normal-hearing and 30 hearing-impaired subjects were participated in the experiment.Results: A 300 sentence corpus was established and 78 sentences with better homogeneity were selected from it. After the equivalence and the test-retest reliability was established for the group materials, 11 equivalent lists for research and clinical use were chosen. The SNR-50 value for these sentences was -2 dB for normal-hearing people, and the formula was defined as "SNR loss=24.5-correct words". The classification of SNR loss was preliminarily quantified as: normal (≤ -2 dB), mild (-2 to 10 dB), moderate (10 to 20 dB) and severe (≥ 20 dB). Conclusions:The M-Quick SIN test provided us 11 equivalent test lists (each list had 6 sentences and 30 key words) and 2 practice lists for testing normal-hearing and hearing-impaired people. The normal value of SNR-50 was -2 dB SNR, and the 6 SNRs: 20, 15, 10, 5, 0, -5 dB SNR were determined to test SNR loss for the M-Quick SIN.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of the Mandarin Quick Speech-in-Noise Test Materials in Mainland China

Zhou¹,

Hua²,

Wang³

et al. 2017

J Phonet and Audiol

View full text Add to dashboard Cite

show abstract

“…Due to this effect, listeners with similar audiograms may have vastly different abilities to understand speech in noise (Killion & Niquette, 2000). A test of speech recognition in noise could provide a means to quantify this ability.…”

Section: Validitymentioning

confidence: 99%

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

Theunissen

Swanepoel

Hanekom

2009

International Journal of Audiology

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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.

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“…The average score for two lists was then taken as the participant's total score. To determine the listener's signal-to-noise ratio loss (SNR loss), the total score was subtracted from 25.5, the average standardized performance of normal hearing listeners (Killion & Niquette, 2000). The SNR loss indicates how much more intense the target speech level must be relative to a normal SNR to recognize the target sentences with 50% accuracy (Killion & Niquette, 2000).…”

Section: Appendix B)mentioning

confidence: 99%

Processing of speech in complex listening environments by individuals with obscure auditory dysfunction

Block

Gordon‐Salant

Hawley

et al. 2006

The Journal of the Acoustical Society of America

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Obscure auditory dysfunction (OAD) is a disorder characterized by patient report of excessive amounts of difficulty understanding speech in the presence of background noise, despite relatively normal hearing sensitivity. It has been hypothesized that OAD may be the result of mild cochlear dysfunction, central auditory processing deficits, and/or psychological disorders. To evaluate auditory processing aspects of this disorder, speech recognition was measured in complex listening conditions for 10 normal-hearing persons with self-reported problems understanding speech in noisy environments. Ten normal-hearing listeners without reported difficulty hearing speech in noise served as controls. Each participant completed a standard audiometric evaluation, the QuickSIN test (standard clinical test of speech recognition in noise), and experimental speech recognition measures in simulated background environments, which included a range and combination of competitor stimuli presented in monaural and binaural conditions. The results show that the OAD participants had poorer overall speech recognition abilities in noise than did control participants for the experimental speech recognition tasks. The pattern of performance deficits suggests that the speech-understanding problems of these OAD participants are not attributable to abnormally poor binaural hearing or to a reduction in masking release. Further, performance deficits exhibited by listeners with OAD were not identified by a standard clinical speech-in-noise measure.

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What can the pure-tone audiogram tell us about a patientʼs SNR loss?

Cited by 119 publications

References 0 publications

Development and Evaluation of the Mandarin Quick Speech-in-Noise Test Materials in Mainland China

Development and Evaluation of the Mandarin Quick Speech-in-Noise Test Materials in Mainland China

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

Processing of speech in complex listening environments by individuals with obscure auditory dysfunction

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