Textile machinery. Noise test code

2015 ◽  
Keyword(s):  
Noise Test

Can Behavioral Speech-In-Noise Tests Improve the Quality of Hearing Aid Fittings?

2011 ◽  
Vol 7 (1) ◽  
pp. 8-14
Author(s):  
Robert Moore ◽  
Susan Gordon-Hickey
Keyword(s):  
Working Memory ◽  
Speech Perception ◽  
Performance Test ◽  
Hearing Aid ◽  
Speech Perception In Noise ◽  
Speech In Noise ◽  
Acceptable Noise Level ◽  
Perceptual Performance ◽  
Noise Test

The purpose of this article is to propose 4 dimensions for consideration in hearing aid fittings and 4 tests to evaluate those dimensions. The 4 dimensions and tests are (a) working memory, evaluated by the Revised Speech Perception in Noise test (Bilger, Nuetzel, & Rabinowitz, 1984); (b) performance in noise, evaluated by the Quick Speech in Noise test (QSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004); (c) acceptance of noise, evaluated by the Acceptable Noise Level test (ANL; Nabelek, Tucker, & Letowski, 1991); and (d) performance versus perception, evaluated by the Perceptual–Performance test (PPT; Saunders & Cienkowski, 2002). The authors discuss the 4 dimensions and tests in the context of improving the quality of hearing aid fittings.

scholarly journals Effect of Speech-to-Noise Ratio and Luminance on a Range of Current and Potential Pupil Response Measures to Assess Listening Effort

2021 ◽  
Vol 25 ◽  
pp. 233121652110093
Author(s):  
Patrycja Książek ◽  
Adriana A. Zekveld ◽  
Dorothea Wendt ◽  
Lorenz Fiedler ◽  
Thomas Lunner ◽  
...  
Keyword(s):  
Time Course ◽  
Principal Component ◽  
Growth Curve Analysis ◽  
Listening Effort ◽  
Data Set ◽  
Holistic View ◽  
Hearing Research ◽  
Speech In Noise ◽  
Noise Test ◽  
Noise Ratio

In hearing research, pupillometry is an established method of studying listening effort. The focus of this study was to evaluate several pupil measures extracted from the Task-Evoked Pupil Responses (TEPRs) in speech-in-noise test. A range of analysis approaches was applied to extract these pupil measures, namely (a) pupil peak dilation (PPD); (b) mean pupil dilation (MPD); (c) index of pupillary activity; (d) growth curve analysis (GCA); and (e) principal component analysis (PCA). The effect of signal-to-noise ratio (SNR; Data Set A: –20 dB, –10 dB, +5 dB SNR) and luminance (Data Set B: 0.1 cd/m2, 360 cd/m2) on the TEPRs were investigated. Data Sets A and B were recorded during a speech-in-noise test and included TEPRs from 33 and 27 normal-hearing native Dutch speakers, respectively. The main results were as follows: (a) A significant effect of SNR was revealed for all pupil measures extracted in the time domain (PPD, MPD, GCA, PCA); (b) Two time series analysis approaches (GCA, PCA) provided modeled temporal profiles of TEPRs (GCA); and time windows spanning subtasks performed in a speech-in-noise test (PCA); and (c) All pupil measures revealed a significant effect of luminance. In conclusion, multiple pupil measures showed similar effects of SNR, suggesting that effort may be reflected in multiple aspects of TEPR. Moreover, a direct analysis of the pupil time course seems to provide a more holistic view of TEPRs, yet further research is needed to understand and interpret its measures. Further research is also required to find pupil measures less sensitive to changes in luminance.

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