Selecting the Optimal FM System for Children With Cochlear Implants

2008 ◽  
Vol 18 (1) ◽  
pp. 19-24
Author(s):  
Erin C. Schafer
Keyword(s):  
Speech Recognition ◽  
Cochlear Implants ◽  
Empirical Research ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Evidence Based ◽  
Signal To Noise ◽  
Speech Processor ◽  
System Input ◽  
Optimal Type

Children who use cochlear implants experience significant difficulty hearing speech in the presence of background noise, such as in the classroom. To address these difficulties, audiologists often recommend frequency-modulated (FM) systems for children with cochlear implants. The purpose of this article is to examine current empirical research in the area of FM systems and cochlear implants. Discussion topics will include selecting the optimal type of FM receiver, benefits of binaural FM-system input, importance of DAI receiver-gain settings, and effects of speech-processor programming on speech recognition. FM systems significantly improve the signal-to-noise ratio at the child's ear through the use of three types of FM receivers: mounted speakers, desktop speakers, or direct-audio input (DAI). This discussion will aid audiologists in making evidence-based recommendations for children using cochlear implants and FM systems.

Evaluation of Speech Recognition in Noise with Cochlear Implants and Dynamic FM

2009 ◽  
Vol 20 (07) ◽  
pp. 409-421 ◽  
Author(s):  
Jace Wolfe ◽  
Erin C. Schafer ◽  
Benjamin Heldner ◽  
Hans Mülder ◽  
Emily Ward ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Cochlear Implants ◽  
Noise Level ◽  
Repeated Measures ◽  
Group Performance ◽  
Signal To Noise Ratio ◽  
Speech Processor ◽  
Repeated Measures Design ◽  
Hearing In Noise ◽  
Speech Recognition In Noise

Background: Use of personal frequency-modulated (FM) systems significantly improves speech recognition in noise for users of cochlear implants (CIs). Previous studies have shown that the most appropriate gain setting on the FM receiver may vary based on the listening situation and the manufacturer of the CI system. Unlike traditional FM systems with fixed-gain settings, Dynamic FM automatically varies the gain of the FM receiver with changes in the ambient noise level. There are no published reports describing the benefits of Dynamic FM use for CI recipients or how Dynamic FM performance varies as a function of CI manufacturer. Purpose: To evaluate speech recognition of Advanced Bionics Corporation or Cochlear Corporation CI recipients using Dynamic FM vs. a traditional FM system and to examine the effects of Autosensitivity on the FM performance of Cochlear Corporation recipients. Research Design: A two-group repeated-measures design. Participants were assigned to a group according to their type of CI. Study Sample: Twenty-five subjects, ranging in age from 8 to 82 years, met the inclusion criteria for one or more of the experiments. Thirteen subjects used Advanced Bionics Corporation, and 12 used Cochlear Corporation implants. Intervention: Speech recognition was assessed while subjects used traditional, fixed-gain FM systems and Dynamic FM systems. Data Collection and Analysis: In Experiments 1 and 2, speech recognition was evaluated with a traditional, fixed-gain FM system and a Dynamic FM system using the Hearing in Noise Test sentences in quiet and in classroom noise. A repeated-measures analysis of variance (ANOVA) was used to evaluate effects of CI manufacturer (Advanced Bionics and Cochlear Corporation), type of FM system (traditional and dynamic), noise level, and use of Autosensitivity for users of Cochlear Corporation implants. Experiment 3 determined the effects of Autosensitivity on speech recognition of Cochlear Corporation implant recipients when listening through the speech processor microphone with the FM system muted. A repeated-measures ANOVA was used to examine the effects of signal-to-noise ratio and Autosensitivity. Results: In Experiment 1, use of Dynamic FM resulted in better speech recognition in noise for Advanced Bionics recipients relative to traditional FM at noise levels of 65, 70, and 75 dB SPL. Advanced Bionics recipients obtained better speech recognition in noise with FM use when compared to Cochlear Corporation recipients. When Autosensitivity was enabled in Experiment 2, the performance of Cochlear Corporation recipients was equivalent to that of Advanced Bionics recipients, and Dynamic FM was significantly better than traditional FM. Results of Experiment 3 indicate that use of Autosensitivity improves speech recognition in noise of signals directed to the speech processor relative to no Autosensitivity. Conclusions: Dynamic FM should be considered for use with persons with CIs to improve speech recognition in noise. At default CI settings, FM performance is better for Advanced Bionics recipients when compared to Cochlear Corporation recipients, but use of Autosensitivity by Cochlear Corporation users results in equivalent group performance.

Cochlear implant patients' speech understanding in background noise: effect of mismatch between electrode assigned frequencies and perceived pitch

2010 ◽  
Vol 124 (8) ◽  
pp. 828-834 ◽  
Author(s):  
W Di Nardo ◽  
A Scorpecci ◽  
S Giannantonio ◽  
F Cianfrone ◽  
C Parrilla ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Cochlear Implant ◽  
Cochlear Implants ◽  
Signal To Noise Ratio ◽  
Residual Hearing ◽  
Speech Understanding ◽  
Signal To Noise ◽  
Electrode Pitch ◽  
Noisy Conditions ◽  
Stimulation Of

AbstractObjective:To assess the electrode pitch function in a series of adults with postlingually implanted cochlear implants and with contralateral residual hearing, in order to investigate the correlation between the degree of frequency map mismatch and the subjects' speech understanding in quiet and noisy conditions.Design:Case series.Subjects:Seven postlingually deafened adults with cochlear implants, all with detectable contralateral residual hearing. Subjects' electrode pitch function was assessed by means of a pitch-matching test, in which they were asked to match an acoustic pitch (pure tones delivered to the non-implanted ear by an audiometer) to a perceived ‘pitch’ elicited by stimulation of the cochlear implant electrodes. A mismatch score was calculated for each subject. Speech recognition was tested using lists of sentences presented in quiet conditions and at +10, 0 and 5 dB HL signal-to-noise ratio levels (i.e. noise 10 dB HL lower than signal, noise as loud as signal and noise 5 dB HL higher than signal, respectively). Correlations were assessed using a linear regression model, with significance set at p < 0.05.Results:All patients presented some degree of mismatch between the acoustic frequencies assigned to their implant electrodes and the pitch elicited by stimulation of the same electrode, with high between-individual variability. A significant correlation (p < 0.005) was found between mismatch and speech recognition scores at +10 and 0 dB HL signal-to-noise ratio levels (r2 = 0.91 and 0.89, respectively).Conclusion:The mismatch between frequencies allocated to electrodes and the pitch perceived on stimulation of the same electrodes could partially account for our subjects' difficulties with speech understanding in noisy conditions. We suggest that these subjects could benefit from mismatch correction, through a procedure allowing individualised reallocation of frequency bands to electrodes.

Effects of Fundamental Frequency Contours on Sentence Recognition in Mandarin-Speaking Children With Cochlear Implants

2020 ◽  
Vol 63 (11) ◽  
pp. 3855-3864
Author(s):  
Wanting Huang ◽  
Lena L. N. Wong ◽  
Fei Chen ◽  
Haihong Liu ◽  
Wei Liang
Keyword(s):  
Cochlear Implants ◽  
Fundamental Frequency ◽  
Signal To Noise Ratio ◽  
Lexical Tone ◽  
Signal To Noise ◽  
Sentence Recognition ◽  
Test Conditions ◽  
Age Appropriate ◽  
F0 Contour ◽  
Appropriate Sentences

Purpose Fundamental frequency (F0) is the primary acoustic cue for lexical tone perception in tonal languages but is processed in a limited way in cochlear implant (CI) systems. The aim of this study was to evaluate the importance of F0 contours in sentence recognition in Mandarin-speaking children with CIs and find out whether it is similar to/different from that in age-matched normal-hearing (NH) peers. Method Age-appropriate sentences, with F0 contours manipulated to be either natural or flattened, were randomly presented to preschool children with CIs and their age-matched peers with NH under three test conditions: in quiet, in white noise, and with competing sentences at 0 dB signal-to-noise ratio. Results The neutralization of F0 contours resulted in a significant reduction in sentence recognition. While this was seen only in noise conditions among NH children, it was observed throughout all test conditions among children with CIs. Moreover, the F0 contour-induced accuracy reduction ratios (i.e., the reduction in sentence recognition resulting from the neutralization of F0 contours compared to the normal F0 condition) were significantly greater in children with CIs than in NH children in all test conditions. Conclusions F0 contours play a major role in sentence recognition in both quiet and noise among pediatric implantees, and the contribution of the F0 contour is even more salient than that in age-matched NH children. These results also suggest that there may be differences between children with CIs and NH children in how F0 contours are processed.

scholarly journals Research on Speaker Recognition of DRNN in Different Noise Environment

2020 ◽  
Author(s):  
chaofeng lan ◽  
yuanyuan Zhang ◽  
hongyun Zhao
Keyword(s):  
Neural Network ◽  
Speech Recognition ◽  
Recurrent Neural Network ◽  
Speaker Recognition ◽  
Signal To Noise Ratio ◽  
Recognition Rate ◽  
Noisy Environment ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Improved Model

Abstract This paper draws on the training method of Recurrent Neural Network (RNN), By increasing the number of hidden layers of RNN and changing the layer activation function from traditional Sigmoid to Leaky ReLU on the input layer, the first group and the last set of data are zero-padded to enhance the effective utilization of data such that the improved reduction model of Denoise Recurrent Neural Network (DRNN) with high calculation speed and good convergence is constructed to solve the problem of low speaker recognition rate in noisy environment. According to this model, the random semantic speech signal with a sampling rate of 16 kHz and a duration of 5 seconds in the speech library is studied. The experimental settings of the signal-to-noise ratios are − 10dB, -5dB, 0dB, 5dB, 10dB, 15dB, 20dB, 25dB. In the noisy environment, the improved model is used to denoise the Mel Frequency Cepstral Coefficients (MFCC) and the Gammatone Frequency Cepstral Coefficents (GFCC), impact of the traditional model and the improved model on the speech recognition rate is analyzed. The research shows that the improved model can effectively eliminate the noise of the feature parameters and improve the speech recognition rate. When the signal-to-noise ratio is low, the speaker recognition rate can be more obvious. Furthermore, when the signal-to-noise ratio is 0dB, the speaker recognition rate of people is increased by 40%, which can be 85% improved compared with the traditional speech model. On the other hand, with the increase in the signal-to-noise ratio, the recognition rate is gradually increased. When the signal-to-noise ratio is 15dB, the recognition rate of speakers is 93%.

Frequency Importance Functions in Quiet and Noise for Adults With Cochlear Implants

2015 ◽  
Vol 24 (4) ◽  
pp. 477-486 ◽  
Author(s):  
Douglas P. Sladen ◽  
Todd. A. Ricketts
Keyword(s):  
Cochlear Implants ◽  
Signal To Noise Ratio ◽  
Small Sample Size ◽  
Normal Hearing ◽  
Small Sample ◽  
Equal Weight ◽  
Signal To Noise ◽  
Speech Spectrum ◽  
Noisy Conditions ◽  
Listening In Noise

Purpose Several studies have been devoted to understanding the frequency information available to adult users of cochlear implants when listening in quiet. The objective of this study was to construct frequency importance functions for a group of adults with cochlear implants and a group of adults with normal hearing both in quiet and in a +10 dB signal-to-noise ratio. Method Two groups of adults, 1 with cochlear implants and 1 with normal hearing, were asked to identify nonsense syllables in quiet and in the presence of 6-talker babble while “holes” were systematically created in the speech spectrum. Frequency importance functions were constructed. Results Results showed that adults with normal hearing placed greater weight on bands 1, 3, and 4 than on bands 2, 5, and 6, whereas adults with cochlear implants placed equal weight on all bands. The frequency importance functions for each group did not differ between listening in quiet and listening in noise. Conclusions Adults with cochlear implants assign perceptual weight toward different frequency bands, though the weight assignment does not differ between quiet and noisy conditions. Generalizing these results to the broader population of adults with implants is constrained by a small sample size.

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.

scholarly journals Improved deconvolution of very weak confocal signals

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 787 ◽  
Author(s):  
Kasey J. Day ◽  
Patrick J. La Rivière ◽  
Talon Chandler ◽  
Vytas P. Bindokas ◽  
Nicola J. Ferrier ◽  
...  
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Time Lapse ◽  
Confocal Image ◽  
Signal To Noise ◽  
4D Imaging ◽  
Fluorescence Images ◽  
Gaussian Blur ◽  
Imaging Conditions

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

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.

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