Validation of the noise reduction index (NRI) as an estimate of the signal‐to‐noise ratio change of a mixed signal by a hearing aid

2007 ◽  
Vol 121 (5) ◽  
pp. 3186-3186 ◽  
Author(s):  
Robert M. Ghent ◽  
Michael J. Nilsson ◽  
Victor H. Bray
Keyword(s):  
Noise Reduction ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Signal To Noise ◽  
Mixed Signal ◽  
Ratio Change ◽  
Noise Ratio ◽  
Reduction Index

scholarly journals Noise reduction and signal-to-noise ratio improvement of atomic magnetometers with optical gradiometer configurations

2015 ◽  
Vol 23 (5) ◽  
pp. 6976 ◽  
Author(s):  
Keigo Kamada ◽  
Yosuke Ito ◽  
Sunao Ichihara ◽  
Natsuhiko Mizutani ◽  
Tetsuo Kobayashi
Keyword(s):  
Noise Reduction ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

Threshold Noise Reduction Research of Improved EEMD Method

2012 ◽  
Vol 226-228 ◽  
pp. 237-240 ◽  
Author(s):  
Mei Jun Zhang ◽  
Hao Chen ◽  
Chuang Wang ◽  
Qing Cao
Keyword(s):  
Noise Reduction ◽  
Signal To Noise Ratio ◽  
Frequency Noise ◽  
Signal To Noise ◽  
Time Frequency ◽  
Noise Ratio ◽  
Reduction Effect ◽  
Eemd Method ◽  
Simulation Signal ◽  
Improved Eemd

In order to extract effectively detection signals in the noise background for non-stationary signal.On the basis of EEMD, improved EEMD is put forward, the improve EEMD threshold noise reduction is researched in this paper.The simulation signal compared the noise reduction effect of the wavelet,EMD,EEMD,and the improved EEMD. The improved EEMD threshold noise reduction have the best noise reduction result , the highest signal-to-noise ratio, the smallest standard deviation error.After the improved EEMD threshold noise reduction , the measurement signal time domain waveform smooth. More high frequency noise was obviously reduced in Hilbert time- frequency spectrum. Signal-to-noise ratio significantly improve, and signal characteristics are very clear.

A Test to Measure Subjective and Objective Speech Intelligibility

2002 ◽  
Vol 13 (01) ◽  
pp. 038-049 ◽  
Author(s):  
Gabrielle H. Saunders ◽  
Kathleen M. Cienkowski
Keyword(s):  
Speech Intelligibility ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Clinical Tool ◽  
Signal To Noise ◽  
Speech Reception ◽  
Measurement Signal ◽  
Perceptual Performance ◽  
Noise Ratio ◽  
Performance Discrepancy

Measurement of hearing aid outcome is particularly difficult because there are numerous dimensions to consider (e.g., performance, satisfaction, benefit). Often there are discrepancies between scores in these dimensions. It is difficult to reconcile these discrepancies because the materials and formats used to measure each dimension are so very different. We report data obtained with an outcome measure that examines both objective and subjective dimensions with the same test format and materials and gives results in the same unit of measurement (signal-to-noise ratio). Two variables are measured: a “performance” speech reception threshold and a “perceptual” speech reception threshold. The signal-to-noise ratio difference between these is computed to determine the perceptual-performance discrepancy (PPDIS). The results showed that, on average, 48 percent of the variance in subjective ratings of a hearing aid could be explained by a combination of the performance speech reception threshold and the PPDIS. These findings suggest that the measure is potentially a valuable clinical tool.

scholarly journals Consistency of Hearing Aid Setting Preference in Simulated Real-World Environments: Implications for Trainable Hearing Aids

2020 ◽  
Vol 24 ◽  
pp. 233121652093339
Author(s):  
Els Walravens ◽  
Gitte Keidser ◽  
Louise Hickson
Keyword(s):  
Hearing Aids ◽  
Real World ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Traffic Noise ◽  
Fine Tuning ◽  
Signal To Noise ◽  
Acoustic Environment ◽  
Change Environment ◽  
Noise Ratio

Trainable hearing aids let users fine-tune their hearing aid settings in their own listening environment: Based on consistent user-adjustments and information about the acoustic environment, the trainable aids will change environment-specific settings to the user’s preference. A requirement for effective fine-tuning is consistency of preference for similar settings in similar environments. The aim of this study was to evaluate consistency of preference for settings differing in intensity, gain-frequency slope, and directionality when listening in simulated real-world environments and to determine if participants with more consistent preferences could be identified based on profile measures. A total of 52 adults (63–88 years) with hearing varying from normal to a moderate sensorineural hearing loss selected their preferred setting from pairs differing in intensity (3 or 6 dB), gain-frequency slope (±1.3 or ± 2.7 dB/octave), or directionality (omnidirectional vs. cardioid) in four simulated real-world environments: traffic noise, a monologue in traffic noise at 5 dB signal-to-noise ratio, and a dialogue in café noise at 5 and at 0 dB signal-to-noise ratio. Forced-choice comparisons were made 10 times for each combination of pairs of settings and environment. Participants also completed nine psychoacoustic, cognitive, and personality measures. Consistency of preference, defined by a setting preferred at least 9 out of 10 times, varied across participants. More participants obtained consistent preferences for larger differences between settings and less difficult environments. The profile measures did not predict consistency of preference. Trainable aid users could benefit from counselling to ensure realistic expectations for particular adjustments and listening situations.

Effects of Adaptive Hearing Aid Directionality and Noise Reduction on Masked Speech Recognition for Children Who Are Hard of Hearing

2019 ◽  
Vol 28 (1) ◽  
pp. 101-113 ◽  
Author(s):  
Jenna M. Browning ◽  
Emily Buss ◽  
Mary Flaherty ◽  
Tim Vallier ◽  
Lori J. Leibold
Keyword(s):  
Speech Recognition ◽  
Hearing Aids ◽  
Hard Of Hearing ◽  
Signal To Noise Ratio ◽  
Hearing Aid ◽  
Normal Hearing ◽  
Signal To Noise ◽  
Open Set ◽  
Fully Adaptive ◽  
Noise Ratio

Purpose The purpose of this study was to evaluate speech-in-noise and speech-in-speech recognition associated with activation of a fully adaptive directional hearing aid algorithm in children with mild to severe bilateral sensory/neural hearing loss. Method Fourteen children (5–14 years old) who are hard of hearing participated in this study. Participants wore laboratory hearing aids. Open-set word recognition thresholds were measured adaptively for 2 hearing aid settings: (a) omnidirectional (OMNI) and (b) fully adaptive directionality. Each hearing aid setting was evaluated in 3 listening conditions. Fourteen children with normal hearing served as age-matched controls. Results Children who are hard of hearing required a more advantageous signal-to-noise ratio than children with normal hearing to achieve comparable performance in all 3 conditions. For children who are hard of hearing, the average improvement in signal-to-noise ratio when comparing fully adaptive directionality to OMNI was 4.0 dB in noise, regardless of target location. Children performed similarly with fully adaptive directionality and OMNI settings in the presence of the speech maskers. Conclusions Compared to OMNI, fully adaptive directionality improved speech recognition in steady noise for children who are hard of hearing, even when they were not facing the target source. This algorithm did not affect speech recognition when the background noise was speech. Although the use of hearing aids with fully adaptive directionality is not proposed as a substitute for remote microphone systems, it appears to offer several advantages over fixed directionality, because it does not depend on children facing the target talker and provides access to multiple talkers within the environment. Additional experiments are required to further evaluate children's performance under a variety of spatial configurations in the presence of both noise and speech maskers.

scholarly journals Noise reduction with reflection supervirtual interferometry

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. V249-V256
Author(s):  
Kai Lu ◽  
Zhaolun Liu ◽  
Sherif Hanafy ◽  
Gerard Schuster
Keyword(s):  
Noise Reduction ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Data Set ◽  
Reflection Data ◽  
The Poor ◽  
The Earth ◽  
The Common ◽  
Noise Ratio

To image deeper portions of the earth, geophysicists must record reflection data with much greater source-receiver offsets. The problem with these data is that the signal-to-noise ratio (S/N) significantly diminishes with greater offset. In many cases, the poor S/N makes the far-offset reflections imperceptible on the shot records. To mitigate this problem, we have developed supervirtual reflection interferometry (SVI), which can be applied to far-offset reflections to significantly increase their S/N. The key idea is to select the common pair gathers where the phases of the correlated reflection arrivals differ from one another by no more than a quarter of a period so that the traces can be coherently stacked. The traces are correlated and summed together to create traces with virtual reflections, which in turn are convolved with one another and stacked to give the reflection traces with much stronger S/Ns. This is similar to refraction SVI except far-offset reflections are used instead of refractions. The theory is validated with synthetic tests where SVI is applied to far-offset reflection arrivals to significantly improve their S/N. Reflection SVI is also applied to a field data set where the reflections are too noisy to be clearly visible in the traces. After the implementation of reflection SVI, the normal moveout velocity can be accurately picked from the SVI-improved data, leading to a successful poststack migration for this data set.

scholarly journals PEMILIHAN METODE PENGURANGAN NOISE PADA CITRA ULTRASONOGRAFI OVARIUM

2020 ◽  
Vol 15 (1) ◽  
pp. 13
Author(s):  
Eliyani Eliyani ◽  
Ahmad Riyadi Maulana
Keyword(s):  
Noise Reduction ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Median Filtering ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

Pengurangan noise merupakan upaya untuk memperbaiki kualitas citra yang akan memudahkan tahapan selanjutnya dalam pengolahan citra. Noise Reduction atau mengurangi noise untuk menghasilkan citra lebih baik sehingga informasi data citra tidak hilang dan citra dapat diintepretasikan oleh mata manusia. Penelitian ini menggunakan data gambar ultrasonografi ovarium untuk membantu menganalisa kondisi kesehatan ovarium perempuan. Gambar ultrasonografi ovarium biasanya terdapat noise, metode pengurangan noise yang akan digunakan pada penelitian ini adalah Median Filtering dan Adaptive Median Filtering. Hasil filtering dari 2 metode tersebut akan dibandingkan menggunakan Mean Square Error(MSE) dan Peak Signal To Noise Ratio(PNSR). Ukuran kernel untuk Median Filtering dan Adaptive Median Filtering dipilih sebagai 3x3, 5x5, dan 7x7. Penelitian ini menghasilkan metode filtering dengan kinerja terbaik yaitu Adaptive Median Filtering dengan ukuran window 5x5 yang ditunjukan dari nilai Mean Square Error dan Peak Signal To Noise Ratio .

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