Speech in noise testing before and after grommet insertion

2012 ◽  
Vol 126 (10) ◽  
pp. 1010-1015 ◽  
Author(s):  
V Possamai ◽  
G Kirk ◽  
A Scott ◽  
D Skinner
Keyword(s):  
Small Group ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Sound Field ◽  
Noise Signal ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Before And After ◽  
Noise Test ◽  
Noise Ratio

AbstractObjectives:To assess the feasibility of designing and implementing a speech in noise test in children before and after grommet insertion, and to analyse the results of such a test in a small group of children.Methods:Twelve children aged six to nine years who were scheduled to undergo grommet insertion were identified. They underwent speech in noise testing before and after grommet insertion. This testing used Arthur Boothroyd word lists read at 60 dB in four listening conditions presented in a sound field: firstly in quiet conditions, then in signal to noise ratios of +10 (50 dB background noise), 0 (60 dB) and −10 (70 dB).Results:Mean phoneme scores were: in quiet conditions, 28.1 pre- and 30 post-operatively (p = 0.04); in 50 dB background noise (signal to noise ratio +10), 24.2 pre- and 29 post-operatively (p < 0.01); in 60 dB background noise (signal to noise ratio 0), 22.6 pre- and 27.5 post-operatively (p = 0.06); and in 70 dB background noise (signal to noise ratio −10), 13.9 pre- and 21 post-operatively (p = 0.05).Conclusion:This small study suggests that speech in noise testing is feasible in this scenario. Our small group of children demonstrated a significant improvement in speech in noise scores following grommet insertion. This is likely to translate into a significant advantage in the educational environment.

Development of a quick speech-in-noise test for measuring signal-to-noise ratio loss in normal-hearing and hearing-impaired listeners

2004 ◽  
Vol 116 (4) ◽  
pp. 2395-2405 ◽  
Author(s):  
Mead C. Killion ◽  
Patricia A. Niquette ◽  
Gail I. Gudmundsen ◽  
Lawrence J. Revit ◽  
Shilpi Banerjee
Keyword(s):  
Signal To Noise Ratio ◽  
Normal Hearing ◽  
Hearing Impaired ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Noise Test ◽  
Noise Ratio ◽  
Measuring Signal

Homogeneity of the 18 QuickSIN™ Lists

2006 ◽  
Vol 17 (03) ◽  
pp. 157-167 ◽  
Author(s):  
Rachel A. McArdle ◽  
Richard H. Wilson
Keyword(s):  
Hearing Loss ◽  
High Performance ◽  
Signal To Noise Ratio ◽  
Normal Hearing ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Performance Variability ◽  
Noise Test ◽  
Noise Ratio ◽  
Db Difference

The purpose of this study was to determine the list equivalency of the 18 QuickSIN™ (Quick Speech in Noise test) lists. Individuals with normal hearing (n = 24) and with sensorineural hearing loss (n = 72) were studied. Mean recognition performances on the 18 lists by the listeners with normal hearing were 2.8 to 4.3 dB SNR (signal-to-noise ratio), whereas the range was 10.0 to 14.3 dB SNR for the listeners with hearing loss. The psychometric functions for each list showed high performance variability across lists for listeners with hearing loss but not for listeners with normal hearing. For listeners with hearing loss, Lists 4, 5, 13, and 16 fell outside of the critical difference. The data from this study suggest nine lists that provide homogenous results for listeners with and without hearing loss. Finally, there was an 8.7 dB difference in performances between the two groups indicating a more favorable signal-to-noise ratio required by the listeners with hearing loss to obtain equal performance.

scholarly journals Super-Resolution Reconstruction of Cell Pseudo-Color Image Based on Raman Technology

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4076
Author(s):  
Yang ◽  
Zhu ◽  
Wang ◽  
Yang ◽  
Wu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectrum ◽  
Background Noise ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Pseudo Color

Raman spectroscopy visualization is a challenging task due to the interference of complex background noise and the number of selected measurement points. In this paper, a super-resolution image reconstruction algorithm for Raman spectroscopy is studied to convert raw Raman data into pseudo-color super-resolution imaging. Firstly, the Raman spectrum data of a single measurement point is measured multiple times to calculate the mean value to remove the random background noise, and innovatively introduce the Retinex algorithm and the median filtering algorithm which improve the signal-to-noise ratio. The novel method of using deep neural network performs a super-resolution reconstruction operation on the gray image. An adaptive guided filter that automatically adjusts the filter radius and penalty factor is proposed to highlight the contour of the cell, and the super-resolution reconstruction of the pseudo-color image of the Raman spectrum is realized. The average signal-to-noise ratio of the reconstructed pseudo-color image sub-band reaches 14.29 db, and the average value of information entropy reaches 4.30 db. The results show that the Raman-based cell pseudo-color image super-resolution reconstruction algorithm is an effective tool to effectively remove noise and high-resolution visualization. The contrast experiments show that the pseudo-color image Kullback–Leiber (KL) entropy of the color image obtained by the method is small, the boundary is obvious, and the noise is small, which provide technical support for the development of sophisticated single-cell imaging Raman spectroscopy instruments.

Letters: Television signal-to-noise ratio before and after demodulation

1978 ◽  
Vol 48 (9) ◽  
pp. 444
Author(s):  
D. Maurice ◽  
J.W. Allnatt ◽  
George H. Hagn ◽  
B.W. Osborne
Keyword(s):  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Television Signal ◽  
Before And After ◽  
Noise Ratio

Uncertainty and Signal-to-Noise Ratio for Unsteady Background Noise

2018 ◽  
Vol 66 (2) ◽  
pp. 131-141 ◽  
Author(s):  
Wongyu Choi ◽  
Michael B. Pate ◽  
James F. Sweeney
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio
Sign in / Sign up

Export Citation Format

Share Document