An Evaluation of the BKB-SIN, HINT, QuickSIN, and WIN Materials on Listeners With Normal Hearing and Listeners With Hearing Loss

Wilson, Richard H.; McArdle, Rachel; Smith, Sherri L.

doi:10.1044/1092-4388(2007/059)

Cited by 212 publications

(207 citation statements)

References 21 publications

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“…Data of Wilson et al ͑2007͒ show that in multitalker babble masker, the relative slopes of NH and HI psychometric functions depend on the speech material. We found that the performance-SNR functions ͓i.e., P e ͑SNR͒, Fig.…”

Section: Discussionmentioning

confidence: 99%

Consonant recognition loss in hearing impaired listeners

Phatak

Yoon

Gooler

et al. 2009

The Journal of the Acoustical Society of America

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This paper presents a compact graphical method for comparing the performance of individual hearing impaired ͑HI͒ listeners with that of an average normal hearing ͑NH͒ listener on a consonant-by-consonant basis. This representation, named the consonant loss profile ͑CLP͒, characterizes the effect of a listener's hearing loss on each consonant over a range of performance. The CLP shows that the consonant loss, which is the signal-to-noise ratio ͑SNR͒ difference at equal NH and HI scores, is consonant-dependent and varies with the score. This variation in the consonant loss reveals that hearing loss renders some consonants unintelligible, while it reduces noise-robustness of some other consonants. The conventional SNR-loss metric ⌬SNR 50 , defined as the SNR difference at 50% recognition score, is insufficient to capture this variation. The ⌬SNR 50 value is on average 12 dB lower when measured with sentences using standard clinical procedures than when measured with nonsense syllables. A listener with symmetric hearing loss may not have identical CLPs for both ears. Some consonant confusions by HI listeners are influenced by the high-frequency hearing loss even at a presentation level as high as 85 dB sound pressure level.

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Section: Discussionmentioning

confidence: 99%

Consonant recognition loss in hearing impaired listeners

Phatak

Yoon

Gooler

et al. 2009

The Journal of the Acoustical Society of America

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“…The sensitivity and specificity of a test can also be indicated by its ability to separate and WIN (Words In Noise test) showed the greatest difference between normal hearers and those with a hearing impairment, indicating that these two measures may be more sensitive than the BKB-SIN and HINT (Wilson et al, 2007b). They also found that the BKB-SIN and HINT materials were easier and yielded higher scores in both groups of subjects (Wilson et al, 2007b).…”

Section: Sensitivity and Specificitymentioning

confidence: 86%

“…They also found that the BKB-SIN and HINT materials were easier and yielded higher scores in both groups of subjects (Wilson et al, 2007b). This attribute could make these tests more useful in populations where poorer performance is expected, such as cochlear implant candidates or the paediatric population.…”

Section: Sensitivity and Specificitymentioning

confidence: 93%

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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“…For example, a widely used PF in the field of speech intelligibility expresses the fraction of words that are correctly identified in a noisy speech sample as a function of the SNR of the speech sample (Miller et al, 1951). The primary goal of a speech intelligibility test is generally to measure the speech-reception threshold (SRT / ), i.e., the SNR at which a particular fraction, /, of words are correctly identified (Plomp and Mimpen, 1979;Wilson et al, 2007). It is also, however, often important to measure the slope of the PF at the SRT (MacPherson and Akeroyd, 2014;Neuman et al, 2010) and it is this that determines the perceptual benefit that can be obtained by improving the SNR.…”

Section: Introductionmentioning

confidence: 99%

Robust and efficient Bayesian adaptive psychometric function estimation

Doire

Brookes

Naylor

2017

The Journal of the Acoustical Society of America

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The efficient measurement of the threshold and slope of the psychometric function (PF) is an important objective in psychoacoustics. This paper proposes a procedure that combines a Bayesian estimate of the PF with either a look one-ahead or a look two-ahead method of selecting the next stimulus presentation. The procedure differs from previously proposed algorithms in two respects: (i) it does not require the range of possible PF parameters to be specified in advance and (ii) the sequence of probe signal-to-noise ratios optimizes the threshold and slope estimates at a performance level, ϕ, that can be chosen by the experimenter. Simulation results show that the proposed procedure is robust and that the estimates of both threshold and slope have a consistently low bias. Over a wide range of listener PF parameters, the root-mean-square errors after 50 trials were ∼1.2 dB in threshold and 0.14 in log-slope. It was found that the performance differences between the look one-ahead and look two-ahead methods were negligible and that an entropy-based criterion for selecting the next stimulus was preferred to a variance-based criterion

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An Evaluation of the BKB-SIN, HINT, QuickSIN, and WIN Materials on Listeners With Normal Hearing and Listeners With Hearing Loss

Abstract: The QuickSIN and WIN materials are more sensitive measures of recognition performance in background noise than are the BKB-SIN and HINT materials.

Cited by 212 publications

References 21 publications

Consonant recognition loss in hearing impaired listeners

Consonant recognition loss in hearing impaired listeners

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

Robust and efficient Bayesian adaptive psychometric function estimation

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