Sound quality perception of cochlear implant recipients: low-frequency information and foreign-language effect

Author(s):  
Niyazi Ömer Arslan ◽  
Ahmet Alperen Akbulut ◽  
Büşra Köse ◽  
Ayşenur Karaman-Demirel ◽  
Ufuk Derinsu
2012 ◽  
Vol 33 (3) ◽  
pp. 319-327 ◽  
Author(s):  
Alexis T. Roy ◽  
Patpong Jiradejvong ◽  
Courtney Carver ◽  
Charles J. Limb

2016 ◽  
Vol 59 (1) ◽  
pp. 99-109 ◽  
Author(s):  
Jennifer R. Fowler ◽  
Jessica L. Eggleston ◽  
Kelly M. Reavis ◽  
Garnett P. McMillan ◽  
Lina A. J. Reiss

PurposeThe objective was to determine whether speech perception could be improved for bimodal listeners (those using a cochlear implant [CI] in one ear and hearing aid in the contralateral ear) by removing low-frequency information provided by the CI, thereby reducing acoustic–electric overlap.MethodSubjects were adult CI subjects with at least 1 year of CI experience. Nine subjects were evaluated in the CI-only condition (control condition), and 26 subjects were evaluated in the bimodal condition. CIs were programmed with 4 experimental programs in which the low cutoff frequency (LCF) was progressively raised. Speech perception was evaluated using Consonant-Nucleus-Consonant words in quiet, AzBio sentences in background babble, and spondee words in background babble.ResultsThe CI-only group showed decreased speech perception in both quiet and noise as the LCF was raised. Bimodal subjects with better hearing in the hearing aid ear (< 60 dB HL at 250 and 500 Hz) performed best for words in quiet as the LCF was raised. In contrast, bimodal subjects with worse hearing (> 60 dB HL at 250 and 500 Hz) performed similarly to the CI-only group.ConclusionsThese findings suggest that reducing low-frequency overlap of the CI and contralateral hearing aid may improve performance in quiet for some bimodal listeners with better hearing.


2013 ◽  
Vol 134 (5) ◽  
pp. 4235-4235 ◽  
Author(s):  
Shuai Wang ◽  
Xuan Zhong ◽  
Michael F. Dorman ◽  
William A. Yost ◽  
Julie M. Liss

2020 ◽  
Author(s):  
Elad Sagi ◽  
Mahan Azadpour ◽  
Jonathan Neukam ◽  
Nicole Hope Capach ◽  
Mario A. Svirsky

Binaural unmasking, a key feature of normal binaural hearing, refers to the improved intelligibility of masked speech by adding masking noise that facilities perceived spatial separation of target and masker. A question particularly relevant for cochlear implant users with single-sided deafness (SSD-CI) is whether binaural unmasking can still be achieved if the additional masking is distorted. Adding the CI restores some aspects of binaural hearing to these listeners, although binaural unmasking remains limited. Notably, these listeners may experience a mismatch between the frequency information perceived through the CI and that perceived by their normal hearing ear. Employing acoustic simulations of SSD-CI with normal hearing listeners, the present study confirms a previous simulation study that binaural unmasking is severely limited when interaural frequency mismatch between the input frequency range and simulated place of stimulation exceeds 1-2 mm. The present study also shows that binaural unmasking is largely retained when the input frequency range is adjusted to match simulated place of stimulation, even at the expense of removing low-frequency information. This result bears implication for the mechanisms driving the type of binaural unmasking of the present study, as well as for mapping the frequency range of the CI speech processor in SSD-CI users.


1996 ◽  
Vol 25 (2) ◽  
pp. 127-132
Author(s):  
Jerker Rönnberg ◽  
Stefan Samuelsson ◽  
Björn Lyxell ◽  
Stig Arlinger

2021 ◽  
Vol 11 (11) ◽  
pp. 5028
Author(s):  
Miaomiao Sun ◽  
Zhenchun Li ◽  
Yanli Liu ◽  
Jiao Wang ◽  
Yufei Su

Low-frequency information can reflect the basic trend of a formation, enhance the accuracy of velocity analysis and improve the imaging accuracy of deep structures in seismic exploration. However, the low-frequency information obtained by the conventional seismic acquisition method is seriously polluted by noise, which will be further lost in processing. Compressed sensing (CS) theory is used to exploit the sparsity of the reflection coefficient in the frequency domain to expand the low-frequency components reasonably, thus improving the data quality. However, the conventional CS method is greatly affected by noise, and the effective expansion of low-frequency information can only be realized in the case of a high signal-to-noise ratio (SNR). In this paper, well information is introduced into the objective function to constrain the inversion process of the estimated reflection coefficient, and then, the low-frequency component of the original data is expanded by extracting the low-frequency information of the reflection coefficient. It has been proved by model tests and actual data processing results that the objective function of estimating the reflection coefficient constrained by well logging data based on CS theory can improve the anti-noise interference ability of the inversion process and expand the low-frequency information well in the case of a low SNR.


2014 ◽  
Vol 539 ◽  
pp. 141-145
Author(s):  
Shui Li Zhang

This paper presents new theorems Stevens edge detection method based on cognitive psychology on. Firstly, based on the number of the image is decomposed into high-frequency and low-frequency information, and the high-frequency information extracted by subtracting the maximum number of images to the image after the filter, then the amount of high frequency information into psychological cognitive psychology based on Stevenss theorem. The algorithm suppression refined edge after the non-minimum, applications Pillar K-means algorithm to extract image edge. Experimental results show that: the brightness of the image is converted to the amount of psychological edge can better unify under different brightness values.


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