Journal articles: 'Signal processing. Cochlear implants'

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Mehrzad, M., M. D. Abolhassani, A. H. Jafari, J. Alirezaie, and M. Sangargir. "Cochlear Implant Speech Processing Using Wavelet Transform." ISRN Signal Processing 2012 (August 1, 2012): 1–6. http://dx.doi.org/10.5402/2012/628706.

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We present a method for coding speech signals for the simulation of a cochlear implant. The method is based on a wavelet packet decomposition strategy. We used wavelet packet db4 for 7 levels, generated a series of channels with bandwidths exactly the same as nucleus device, and applied an input stimulus to each channel. The processed signal was then reconstructed and compared to the original signal, which preserved the contents to a high percentage. Finally, performance of the wavelet packet decomposition in terms of computational complexity was compared to other commonly used strategies in cochlear implants. The results showed the power of this method in processing of the input signal for implant users with less complexity than other methods, while maintaining the contents of the input signal to a very good extent.

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Laizou, P. C. "Signal-processing techniques for cochlear implants." IEEE Engineering in Medicine and Biology Magazine 18, no. 3 (1999): 34–46. http://dx.doi.org/10.1109/51.765187.

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Nie, Kaibao. "ENHANCED SIGNAL PROCESSING FOR COCHLEAR IMPLANTS." Journal of the Acoustical Society of America 131, no. 3 (2012): 2351. http://dx.doi.org/10.1121/1.3696845.

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Elberling, C. "Discussion of Signal-processing Potentials; Cochlear Implants." Acta Oto-Laryngologica 109, sup469 (January 1, 1990): 164–65. http://dx.doi.org/10.1080/00016489.1990.12088424.

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Tobey, Emily A., Lana Britt, Ann Geers, Philip Loizou, Betty Loy, Peter Roland, Andrea Warner-Czyz, and Charles G. Wright. "Cochlear Implantation Updates: The Dallas Cochlear Implant Program." Journal of the American Academy of Audiology 23, no. 06 (June 2012): 438–45. http://dx.doi.org/10.3766/jaaa.23.6.6.

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This report provides an overview of many research projects conducted by the Dallas Cochlear Implant Program, a joint enterprise between the University of Texas at Dallas, the University of Texas Southwestern Medical Center, and Children’s Medical Center. The studies extend our knowledge of factors influencing communication outcomes in users of cochlear implants. Multiple designs and statistical techniques are used in the studies described including both cross sectional and longitudinal analyses. Sample sizes vary across the studies, and many of the samples represent large populations of children from North America. Multiple statistical techniques are used by the team to analyze outcomes. The team has provided critical information regarding electrode placement, signal processing, and communication outcomes in users of cochlear implants.

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Tyler, Richard S., and Mary W. Lowder. "Audiological Management and Performance of Adult Cochlear-Implant Patients." Ear, Nose & Throat Journal 71, no. 3 (March 1992): 117–28. http://dx.doi.org/10.1177/014556139207100302.

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We review the signal-processing strategies of three of the most common cochlear implants in use today, the single-channel House, the multichannel Nucleus, and the Ineraid devices. The results of 65 postlinguistically-deafened patients tested at The University of Iowa are reviewed. The tests include everyday sound, accent, word and sentence recognition, as well as noise/voice differentiation. For all tests, patients with the Nucleus and Ineraid cochlear implants outperformed those with the House implant. In general, selection criteria should focus on comparing the performance of Patients who have already received an implant. Prelinguistically-deafened adults are typically not good cochlear-impact candidates. Cochlear-implant teams should be aware of the enormous time commitment for testing and rehabilitation of these patients, and be prepared to handle frequent implant breakdowns. Nevertheless, cochlear-implant patients have been helped significantly be these devices.

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S.Hallikar, Rohini, M. Uttarakumari, Padmaraju K, and Yashas D. "Modified Turbo and SDROM Method for Speech Processing for Cochlear Implants." International Journal of Engineering & Technology 7, no. 4.5 (September 22, 2018): 179. http://dx.doi.org/10.14419/ijet.v7i4.5.20040.

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A performance comparison of Signal Dependent Rank Order Mean (SDROM) method of speech signal enhancement with a speech enhancement method which makes use of a Turbo combination and SDROM filter referred to as modified Turbo and SDROM technique is made in this paper. Normally, speech signals are used as inputs to a cochlear implant signal processing unit.Sounds are corrupted by different noises such as AWGN, Impulsive noise and babble. The results are evaluated in terms of enhancements evaluations done by basically three parameters namely correlation coefficient, log spectral distortion (LSD) and segmental signal to noise ratio(SSNR). These parameters are calculated between the processed and the clean signals.. Results prove the superior performance of the new method especially for AWGN corrupted speech.

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Rubinstein, Jay T., and Robert Hong. "Signal Coding in Cochlear Implants: Exploiting Stochastic Effects of Electrical Stimulation." Annals of Otology, Rhinology & Laryngology 112, no. 9_suppl (September 2003): 14–19. http://dx.doi.org/10.1177/00034894031120s904.

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Speech perception in quiet with cochlear implants has increased substantially over the past 17 years. If current trends continue, average monosyllabic word scores will be nearly 80% by 2010. These improvements are due to enhancements in speech processing strategies, to the implantation of patients with more residual hearing and shorter durations of deafness, and to unknown causes. Despite these improvements, speech perception in noise and music perception are still poor in most implant patients. These deficits may be partly due to poor representation of temporal fine structure by current speech processing strategies. It may be possible to improve both this representation and the dynamic range of electrical stimulation through the exploitation of stochastic effects produced by high-rate (eg, 5-kilopulse-per-second) pulse trains. Both the loudness growth and the dynamic range of low-frequency sinusoids have been enhanced via this technique. A laboratory speech processor using this strategy is under development. Although the clinical programming for such an algorithm is likely to be complex, some guidelines for the psychophysical and electrophysiological techniques necessary can be described now.

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Smiljanic, Rajka, and Douglas Sladen. "Acoustic and Semantic Enhancements for Children With Cochlear Implants." Journal of Speech, Language, and Hearing Research 56, no. 4 (August 2013): 1085–96. http://dx.doi.org/10.1044/1092-4388(2012/12-0097).

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Purpose In this study, the authors examined how signal clarity interacts with the use of sentence context information in determining speech-in-noise recognition for children with cochlear implants and children with normal hearing. Method One hundred and twenty sentences in which the final word varied in predictability (high vs. low semantic context) were produced in conversational and clear speech. Nine children with cochlear implants and 9 children with normal hearing completed the sentence-in-noise listening tests and a standardized language measure. Results Word recognition in noise improved significantly for both groups of children for high-predictability sentences in clear speech. Children with normal hearing benefited more from each source of information compared with children with cochlear implants. There was a significant correlation between more developed language skills and the ability to use contextual enhancements. The smaller context gain in clear speech for children with cochlear implants is in accord with the effortfulness hypothesis (McCoy et al., 2005) and points to the cumulative effects of noise throughout the processing system. Conclusion Modifications of the speech signal and the context of the utterances through changes in the talker output hold substantial promise as a communication enhancement technique for both children with cochlear implants and children with normal hearing.

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Nittrouer, Susan, Amanda Caldwell-Tarr, Keri E. Low, and Joanna H. Lowenstein. "Verbal Working Memory in Children With Cochlear Implants." Journal of Speech, Language, and Hearing Research 60, no. 11 (November 9, 2017): 3342–64. http://dx.doi.org/10.1044/2017_jslhr-h-16-0474.

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Purpose Verbal working memory in children with cochlear implants and children with normal hearing was examined. Participants Ninety-three fourth graders (47 with normal hearing, 46 with cochlear implants) participated, all of whom were in a longitudinal study and had working memory assessed 2 years earlier. Method A dual-component model of working memory was adopted, and a serial recall task measured storage and processing. Potential predictor variables were phonological awareness, vocabulary knowledge, nonverbal IQ, and several treatment variables. Potential dependent functions were literacy, expressive language, and speech-in-noise recognition. Results Children with cochlear implants showed deficits in storage and processing, similar in size to those at second grade. Predictors of verbal working memory differed across groups: Phonological awareness explained the most variance in children with normal hearing; vocabulary explained the most variance in children with cochlear implants. Treatment variables explained little of the variance. Where potentially dependent functions were concerned, verbal working memory accounted for little variance once the variance explained by other predictors was removed. Conclusions The verbal working memory deficits of children with cochlear implants arise due to signal degradation, which limits their abilities to acquire phonological awareness. That hinders their abilities to store items using a phonological code.

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Isaiah, Amal, and Kenneth H. Lee. "Cochlear Implants in Children: Recent Advances." International Journal of Head and Neck Surgery 7, no. 2 (2016): 115–19. http://dx.doi.org/10.5005/jp-journals-10001-1275.

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ABSTRACT Cochlear implants (CIs) are the best-performing neural prostheses today. Clinical data have demonstrated that early implantation facilitates advancements in auditory, cognitive and developmental milestones, enabling children to succeed in mainstream schools. With recent improvements in engineering design, signal processing, as well as surgical and rehabilitation techniques, CIs have ushered in expanded candidacy criteria. This review aims to provide a critical evaluation of recent developments in CI strategies --specifically within the areas of implantation of malformed inner ears, outcomes following bilateral CIs, implantation for single-sided deafness and newer, adjuvant biological therapies to augment CI technology. How to cite this article Isaiah A, Lee KH. Cochlear Implants in Children: Recent Advances. Int J Head Neck Surg 2016;7(2):115-119.

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Wagner, Luise, Stefan K. Plontke, and Torsten Rahne. "Perception of Iterated Rippled Noise Periodicity in Cochlear Implant Users." Audiology and Neurotology 22, no. 2 (2017): 104–15. http://dx.doi.org/10.1159/000478649.

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Pitch perception is more challenging for individuals with cochlear implants (CIs) than normal-hearing subjects because the signal processing by CIs is restricted. Processing and perceiving the periodicity of signals may contribute to pitch perception. Whether individuals with CIs can discern pitch within an iterated rippled noise (IRN) signal is still unclear. In a prospective controlled psychoacoustic study with 34 CI users and 15 normal-hearing control subjects, the difference limen between IRN signals with different numbers of iterations was measured. In 7 CI users and 15 normal-hearing control listeners with single-sided deafness, pitch matching between IRN and harmonic complex tones was measured. The pitch onset response (POR) following signal changes from white noise to IRN was measured electrophysiologically. The CI users could discriminate different numbers of iteration in IRN signals, but worse than normal-hearing listeners. A POR was measured for both normal-hearing subjects and CI users increasing with the pitch salience of the IRN. This indicates that the POR could serve as an objective measure to monitor progress during audioverbal therapy after CI surgery.

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Swaminathan, Jayaganesh, Raymond L. Goldsworthy, Patrick M. Zurek, Agnès C. Léger, and Louis D. Braida. "Preliminary evaluation of a physiologically inspired signal processing strategy for cochlear implants." Journal of the Acoustical Society of America 135, no. 4 (April 2014): 2410. http://dx.doi.org/10.1121/1.4877987.

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Fridman, Gene Y. "METHODS AND APPARATUS FOR COCHLEAR IMPLANT SIGNAL PROCESSING." Journal of the Acoustical Society of America 134, no. 5 (2013): 3966. http://dx.doi.org/10.1121/1.4828921.

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Fridman, Gene Y. "Methods And Apparatus For Cochlear Implant Signal Processing." Journal of the Acoustical Society of America 130, no. 5 (2011): 3179. http://dx.doi.org/10.1121/1.3662369.

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Blamey, Peter J. "Adaptive Dynamic Range Optimization (ADRO): A Digital Amplification Strategy for Hearing Aids and Cochlear Implants." Trends in Amplification 9, no. 2 (March 2005): 77–98. http://dx.doi.org/10.1177/108471380500900203.

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Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively.

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Lamia, Bouafif, Ouni Kais, and Ellouze Noureddine. "Performances Study of a New Speech Coding Strategy with Reduced Channels for Cochlear Implants." Open Signal Processing Journal 2, no. 1 (October 23, 2009): 29–39. http://dx.doi.org/10.2174/1876825300902010029.

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Tyler, Richard S., Shelley A. Witt, Camille C. Dunn, and Ann E. Perreau. "A Daily Alternating Method for Comparing Different Signal-Processing Strategies in Hearing Aids and in Cochlear Implants." Journal of the American Academy of Audiology 19, no. 05 (May 2008): 443–54. http://dx.doi.org/10.3766/jaaa.19.5.7.

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Background: Although we always want to select the best signal-processing strategy for our hearing-aid and cochlear-implant patients, no efficient and valid procedure is available. Comparisons in the office are without listening experience, and short-term take-home trials are likely influenced by the order of strategies tried. Purpose: The purpose of this study was to evaluate a new procedure for comparing signal-processing strategies whereby patients listen with one strategy one day and another strategy the next day. They continue this daily comparison for several weeks. We determined (1) if differences existed between strategies without prior listening experience and (2) if performance differences (or lack there of) obtained at the first listening experience are consistent with performance after two to three months of alternating between strategies on a daily basis (equal listening experience). Research Design: Eight subjects were tested pretrial with a vowel, sentence, and spondee recognition test, a localization task, and a quality rating test. They were required to listen to one of two different signal processing strategies alternating between strategies on a daily basis. After one to three months of listening, subjects returned for follow-up testing. Additionally, subjects were asked to make daily ratings and comments in a diary. Results: Pre-trial (no previous listening experience), a clear trend favoring one strategy was observed in four subjects. Four other subjects showed no clear advantage. Post-trial (after alternating daily between strategies), of the four subjects who showed a clear advantage for one signal processing strategy, only one subject showed that same advantage. One subject ended up with an advantage for the other strategy. Post-trial, of the four subjects who showed no advantage for a particular signal processing strategy, three did show an advantage for one strategy over the other. Conclusion: Patients are willing to alternate between signal processing strategies on a daily basis for up to three months in an attempt to determine their optimal strategy. Although some patients showed superior performance with initial fittings (and some did not), the results of pre-trial comparison did not always persist after having equal listening experience. We recommend this daily alternating listening technique when there is interest in determining optimal performance among different signal processing strategies when fitting hearing aids or cochlear implants.

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ÖZBAL BATUK, Merve, Erva DEĞİRMENCİ UZUN, Betül KOSKA, and Merve ÖZSES. "Signal Processing Strategies In Cochlear Implant Systems: A Review of Literature." Kulak Burun Boğaz ve Baş Boyun Cerrahisi Dergisi 29, no. 3 (2021): 222–35. http://dx.doi.org/10.24179/kbbbbc.2021-81939.

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Milczynski, Matthias, Jan Wouters, and Astrid van Wieringen. "Improved fundamental frequency coding in cochlear implant signal processing." Journal of the Acoustical Society of America 125, no. 4 (April 2009): 2260–71. http://dx.doi.org/10.1121/1.3085642.

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Heffer, Leon F., David J. Sly, James B. Fallon, Mark W. White, Robert K. Shepherd, and Stephen J. O'Leary. "Examining the Auditory Nerve Fiber Response to High Rate Cochlear Implant Stimulation: Chronic Sensorineural Hearing Loss and Facilitation." Journal of Neurophysiology 104, no. 6 (December 2010): 3124–35. http://dx.doi.org/10.1152/jn.00500.2010.

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Neural prostheses, such as cochlear and retinal implants, induce perceptual responses by electrically stimulating sensory nerves. These devices restore sensory system function by using patterned electrical stimuli to evoke neural responses. An understanding of their function requires knowledge of the nerves responses to relevant electrical stimuli as well as the likely effects of pathology on nerve function. We describe how sensorineural hearing loss (SNHL) affects the response properties of single auditory nerve fibers (ANFs) to electrical stimuli relevant to cochlear implants. The response of 188 individual ANFs were recorded in response to trains of stimuli presented at 200, 1,000, 2,000, and 5,000 pulse/s in acutely and chronically deafened guinea pigs. The effects of stimulation rate and SNHL on ANF responses during the 0–2 ms period following stimulus onset were examined to minimize the influence of ANF adaptation. As stimulation rate increased to 5,000 pulse/s, threshold decreased, dynamic range increased and first spike latency decreased. Similar effects of stimulation rate were observed following chronic SNHL, although onset threshold and first spike latency were reduced and onset dynamic range increased compared with acutely deafened animals. Facilitation, defined as an increased nerve excitability caused by subthreshold stimulation, was observed in both acute and chronic SNHL groups, although the magnitude of its effect was diminished in the latter. These results indicate that facilitation, demonstrated here using stimuli similar to those used in cochlear implants, influences the ANF response to pulsatile electrical stimulation and may have important implications for cochlear implant signal processing strategies.

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Jensen, Robert C., and Sarah Hargus Ferguson. "Music Perception in Adult Users of Cochlear Implants: A Brief Review." Perspectives on Aural Rehabilitation and Its Instrumentation 22, no. 1 (May 2015): 4–11. http://dx.doi.org/10.1044/arii22.1.4.

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Although cochlear implants (CIs) can provide good speech understanding in quiet, in general, users of CIs have shown poor music perception performance, particularly with regard to pitch (and hence melody). This is primarily due to the limited ability of CI processing strategies and electric stimulation to provide place pitch and fine structure information from the original input signal to the auditory nervous system of the user. Approaches such as current focusing, current steering, enhanced amplitude modulation cues, and optic stimulation have been shown or theorized to assist in music perception, as have musical training programs. This article is a brief review of research related to music perception in adults with CIs, specifically their rhythm, pitch, and melody perception performance; processing strategies that have been or are being developed which might improve their music perception performance; and music training programs that have been shown to improve their music perception performance.

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Goldsworthy, Raymond L. "Temporal envelope cues and simulations of cochlear implant signal processing." Speech Communication 109 (May 2019): 24–33. http://dx.doi.org/10.1016/j.specom.2019.03.003.

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Zheng, Yunfang, Janet Koehnke, and Joan Besing. "Combined Effects of Noise and Reverberation on Sound Localization for Listeners With Normal Hearing and Bilateral Cochlear Implants." American Journal of Audiology 26, no. 4 (December 12, 2017): 519–30. http://dx.doi.org/10.1044/2017_aja-16-0101.

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Purpose This study examined the individual and combined effects of noise and reverberation on the ability of listeners with normal hearing (NH) and with bilateral cochlear implants (BCIs) to localize speech. Method Six adults with BCIs and 10 with NH participated. All subjects completed a virtual localization test in quiet and at 0-, −4-, and −8-dB signal-to-noise ratios (SNRs) in simulated anechoic and reverberant (0.2-, 0.6-, and 0.9-s RT 60 ) environments. BCI users were also tested at +8- and +4-dB SNR. A 3-word phrase was presented at 70 dB SPL from 9 simulated locations in the frontal horizontal plane (±90°), with the noise source at 0°. Results BCIs users had significantly poorer localization than listeners with NH in all conditions. BCI users' performance started to decrease at a higher SNR (+4 dB) and shorter RT 60 (0.2 s) than listeners with NH (−4 dB and 0.6 s). The combination of noise and reverberation began to degrade localization of BCI users at a higher SNR and a shorter RT 60 than listeners with NH. Conclusion The clear effect of noise and reverberation on the performance of BCI users provides information that should be useful for refining cochlear implant processing strategies and developing cochlear implant rehabilitation plans to optimize binaural benefit for BCI users in everyday listening situations.

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Wouters, Jan, Hugh Joseph McDermott, and Tom Francart. "Sound Coding in Cochlear Implants: From electric pulses to hearing." IEEE Signal Processing Magazine 32, no. 2 (March 2015): 67–80. http://dx.doi.org/10.1109/msp.2014.2371671.

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Melo, Tatiana Mendes de, Elisabete Honda Yamaguti, Adriane Lima Mortari Moret, Orozimbo Alves Costa, and Natália Barreto Frederigue Lopes. "Development of auditory and language skills in children using cochlear implants with two signal processing strategies." Brazilian Journal of Otorhinolaryngology 86, no. 6 (November 2020): 720–26. http://dx.doi.org/10.1016/j.bjorl.2019.05.006.

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Kolberg, Elizabeth R., Sterling W. Sheffield, Timothy J. Davis, Linsey W. Sunderhaus, and René H. Gifford. "Cochlear Implant Microphone Location Affects Speech Recognition in Diffuse Noise." Journal of the American Academy of Audiology 26, no. 01 (January 2015): 051–58. http://dx.doi.org/10.3766/jaaa.26.1.6.

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Background: Despite improvements in cochlear implants (CIs), CI recipients continue to experience significant communicative difficulty in background noise. Many potential solutions have been proposed to help increase signal-to-noise ratio in noisy environments, including signal processing and external accessories. To date, however, the effect of microphone location on speech recognition in noise has focused primarily on hearing aid users. Purpose: The purpose of this study was to (1) measure physical output for the T-Mic as compared with the integrated behind-the-ear (BTE) processor mic for various source azimuths, and (2) to investigate the effect of CI processor mic location for speech recognition in semi-diffuse noise with speech originating from various source azimuths as encountered in everyday communicative environments. Research Design: A repeated-measures, within-participant design was used to compare performance across listening conditions. Study Sample: A total of 11 adults with Advanced Bionics CIs were recruited for this study. Data Collection and Analysis: Physical acoustic output was measured on a Knowles Experimental Mannequin for Acoustic Research (KEMAR) for the T-Mic and BTE mic, with broadband noise presented at 0 and 90° (directed toward the implant processor). In addition to physical acoustic measurements, we also assessed recognition of sentences constructed by researchers at Texas Instruments, the Massachusetts Institute of Technology, and the Stanford Research Institute (TIMIT sentences) at 60 dBA for speech source azimuths of 0, 90, and 270°. Sentences were presented in a semi-diffuse restaurant noise originating from the R-SPACE 8-loudspeaker array. Signal-to-noise ratio was determined individually to achieve approximately 50% correct in the unilateral implanted listening condition with speech at 0°. Performance was compared across the T-Mic, 50/50, and the integrated BTE processor mic. Results: The integrated BTE mic provided approximately 5 dB attenuation from 1500–4500 Hz for signals presented at 0° as compared with 90° (directed toward the processor). The T-Mic output was essentially equivalent for sources originating from 0 and 90°. Mic location also significantly affected sentence recognition as a function of source azimuth, with the T-Mic yielding the highest performance for speech originating from 0°. Conclusions: These results have clinical implications for (1) future implant processor design with respect to mic location, (2) mic settings for implant recipients, and (3) execution of advanced speech testing in the clinic.

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Black, F. O., D. J. Lilly, R. J. Peterka, L. P. Fowler, and F. B. Simmons. "Vestibulo-Ocular and Vestibulospinal Function before and after Cochlear Implant Surgery." Annals of Otology, Rhinology & Laryngology 96, no. 1_suppl (January 1987): 106–9. http://dx.doi.org/10.1177/00034894870960s157.

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Vestibular function in cochlear implant candidates varies from normal to total absence of function. In patients with intact vestibular function preoperatively, invasion of the otic capsule places residual vestibular function at risk. Speech-processing strategies that result in large amplitude electrical transients or strategies that employ high amplitude broad frequency carrier signals have the potential for disrupting vestibular function. Five patients were tested with and without electrical stimulation via cochlear electrodes. Two patients experienced subjective vestibular effects that were quickly resolved. No long-term vestibular effects were noted for the two types of second generation cochlear implants evaluated. Histopathological findings from another patient, who had electrically generated vestibular reflex responses to intramodiolar electrodes, indicated that responses elicited were a function of several variables including electrode location, stimulus intensity, stimulus amplitude, and stimulus frequency. Differential auditory, vestibulocolic, and vestibulospinal reflexes were demonstrated from the same electrode as a function of stimulus amplitude, frequency, and duration.

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Deocampo, Joanne A., Gretchen N. L. Smith, William G. Kronenberger, David B. Pisoni, and Christopher M. Conway. "The Role of Statistical Learning in Understanding and Treating Spoken Language Outcomes in Deaf Children With Cochlear Implants." Language, Speech, and Hearing Services in Schools 49, no. 3S (August 14, 2018): 723–39. http://dx.doi.org/10.1044/2018_lshss-stlt1-17-0138.

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Purpose Statistical learning—the ability to learn patterns in environmental input—is increasingly recognized as a foundational mechanism necessary for the successful acquisition of spoken language. Spoken language is a complex, serially presented signal that contains embedded statistical relations among linguistic units, such as phonemes, morphemes, and words, which represent the phonotactic and syntactic rules of language. In this review article, we first review recent work that demonstrates that, in typical language development, individuals who display better nonlinguistic statistical learning abilities also show better performance on different measures of language. We next review research findings that suggest that children who are deaf and use cochlear implants may have difficulties learning sequential input patterns, possibly due to auditory and/or linguistic deprivation early in development, and that the children who show better sequence learning abilities also display improved spoken language outcomes. Finally, we present recent findings suggesting that it may be possible to improve core statistical learning abilities with specialized training and interventions and that such improvements can potentially impact and facilitate the acquisition and processing of spoken language. Method We conducted a literature search through various online databases including PsychINFO and PubMed, as well as including relevant review articles gleaned from the reference sections of other review articles used in this review. Search terms included various combinations of the following: sequential learning, sequence learning, statistical learning, sequence processing, procedural learning, procedural memory, implicit learning, language, computerized training, working memory training, statistical learning training, deaf, deafness, hearing impairment, hearing impaired, DHH, hard of hearing, cochlear implant(s), hearing aid(s), and auditory deprivation. To keep this review concise and clear, we limited inclusion to the foundational and most recent (2005–2018) relevant studies that explicitly included research or theoretical perspectives on statistical or sequential learning. We here summarize and synthesize the most recent and relevant literature to understanding and treating language delays in children using cochlear implants through the lens of statistical learning. Conclusions We suggest that understanding how statistical learning contributes to spoken language development is important for understanding some of the difficulties that children who are deaf and use cochlear implants might face and argue that it may be beneficial to develop novel language interventions that focus specifically on improving core foundational statistical learning skills.

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Jun Yao and Yuan-Ting Zhang. "The application of bionic wavelet transform to speech signal processing in cochlear implants using neural network simulations." IEEE Transactions on Biomedical Engineering 49, no. 11 (November 2002): 1299–309. http://dx.doi.org/10.1109/tbme.2002.804590.

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Blomquist, Christina, Rochelle S. Newman, Yi Ting Huang, and Jan Edwards. "Children With Cochlear Implants Use Semantic Prediction to Facilitate Spoken Word Recognition." Journal of Speech, Language, and Hearing Research 64, no. 5 (May 11, 2021): 1636–49. http://dx.doi.org/10.1044/2021_jslhr-20-00319.

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Purpose Children with cochlear implants (CIs) are more likely to struggle with spoken language than their age-matched peers with normal hearing (NH), and new language processing literature suggests that these challenges may be linked to delays in spoken word recognition. The purpose of this study was to investigate whether children with CIs use language knowledge via semantic prediction to facilitate recognition of upcoming words and help compensate for uncertainties in the acoustic signal. Method Five- to 10-year-old children with CIs heard sentences with an informative verb ( draws ) or a neutral verb ( gets ) preceding a target word ( picture ). The target referent was presented on a screen, along with a phonologically similar competitor ( pickle ). Children's eye gaze was recorded to quantify efficiency of access of the target word and suppression of phonological competition. Performance was compared to both an age-matched group and vocabulary-matched group of children with NH. Results Children with CIs, like their peers with NH, demonstrated use of informative verbs to look more quickly to the target word and look less to the phonological competitor. However, children with CIs demonstrated less efficient use of semantic cues relative to their peers with NH, even when matched for vocabulary ability. Conclusions Children with CIs use semantic prediction to facilitate spoken word recognition but do so to a lesser extent than children with NH. Children with CIs experience challenges in predictive spoken language processing above and beyond limitations from delayed vocabulary development. Children with CIs with better vocabulary ability demonstrate more efficient use of lexical-semantic cues. Clinical interventions focusing on building knowledge of words and their associations may support efficiency of spoken language processing for children with CIs. Supplemental Material https://doi.org/10.23641/asha.14417627

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Tabibi, Sonia, and Hamed Sadjedi. "Adaptive Sample Reduction Techniques for Continuous Interleaved Sampling Strategy in Multi Channel Cochlear Implant." Advanced Materials Research 403-408 (November 2011): 2021–26. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2021.

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CIS (Continuous Interleaved Sampling) strategy in which electrodes stimulus is determined based on extracted information from amplitude of different bands of input signal, is a basis in processing methods in cochlear implant systems. In this paper besides implementing this strategy, methods for improving sample reduction and computational efficiency are also presented. In this case adaptive method according to processing parameters and an input signal has been suggested that due to the use of fewer samples to synthesize the signal is better than the other methods and is significantly efficient.

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Wu, Xihong, Hongwei Qu, Jing Chen, Tianshu Qu, and Liang Li. "Simulated phase‐locking stimulation: An improved signal processing strategy for cochlear implant." Journal of the Acoustical Society of America 117, no. 4 (April 2005): 2397. http://dx.doi.org/10.1121/1.4785964.

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Jaekel, Brittany N., Rochelle S. Newman, and Matthew J. Goupell. "Speech Rate Normalization and Phonemic Boundary Perception in Cochlear-Implant Users." Journal of Speech, Language, and Hearing Research 60, no. 5 (May 24, 2017): 1398–416. http://dx.doi.org/10.1044/2016_jslhr-h-15-0427.

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Purpose Normal-hearing (NH) listeners rate normalize, temporarily remapping phonemic category boundaries to account for a talker's speech rate. It is unknown if adults who use auditory prostheses called cochlear implants (CI) can rate normalize, as CIs transmit degraded speech signals to the auditory nerve. Ineffective adjustment to rate information could explain some of the variability in this population's speech perception outcomes. Method Phonemes with manipulated voice-onset-time (VOT) durations were embedded in sentences with different speech rates. Twenty-three CI and 29 NH participants performed a phoneme identification task. NH participants heard the same unprocessed stimuli as the CI participants or stimuli degraded by a sine vocoder, simulating aspects of CI processing. Results CI participants showed larger rate normalization effects (6.6 ms) than the NH participants (3.7 ms) and had shallower (less reliable) category boundary slopes. NH participants showed similarly shallow slopes when presented acoustically degraded vocoded signals, but an equal or smaller rate effect in response to reductions in available spectral and temporal information. Conclusion CI participants can rate normalize, despite their degraded speech input, and show a larger rate effect compared to NH participants. CI participants may particularly rely on rate normalization to better maintain perceptual constancy of the speech signal.

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Vollmer, Maike, Ralph E. Beitel, and Russell L. Snyder. "Auditory Detection and Discrimination in Deaf Cats: Psychophysical and Neural Thresholds for Intracochlear Electrical Signals." Journal of Neurophysiology 86, no. 5 (November 1, 2001): 2330–43. http://dx.doi.org/10.1152/jn.2001.86.5.2330.

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More than 30,000 hearing-impaired human subjects have learned to use cochlear implants for speech perception and speech discrimination. To understand the basic mechanisms underlying the successful application of contemporary speech processing strategies, it is important to investigate how complex electrical stimuli delivered to the cochlea are processed and represented in the central auditory system. A deaf animal model has been developed that allows direct comparison of psychophysical thresholds with central auditory neuronal thresholds to temporally modulated intracochlear electrical signals in the same animals. Behavioral detection thresholds were estimated in neonatally deafened cats for unmodulated pulse trains (e.g., 30 pulses/s or pps) and sinusoidal amplitude-modulated (SAM) pulse trains (e.g., 300 pps, SAM at 30 Hz; 300/30 AM). Animals were trained subsequently in a discrimination task to respond to changes in the modulation frequency of successive SAM signals (e.g., 300/8 AM vs. 300/30 AM). During acute physiological experiments, neural thresholds to pulse trains were estimated in the inferior colliculus (IC) and the primary auditory cortex (A1) of the anesthetized animals. Psychophysical detection thresholds for unmodulated and SAM pulse trains were virtually identical. Single IC neuron thresholds for SAM pulse trains showed a small but significant increase in threshold (0.4 dB or 15.5 μA) when compared with thresholds for unmodulated pulse trains. The mean difference between psychophysical and minimum neural thresholds within animals was not significant (mean = 0.3 dB). Importantly, cats also successfully discriminated changes in the modulation frequencies of the SAM signals. Performance on the discrimination task was not affected by carrier rate (100, 300, 500, 1,000, or 1,500 pps). These findings indicate that 1) behavioral and neural response thresholds are based on detection of the peak pulse amplitudes of the modulated and unmodulated signals, and 2) discrimination of successive SAM pulse trains is based on temporal resolution of the envelope frequencies. Overall, our animal model provides a robust framework for future studies of behavioral discrimination and central neural temporal processing of electrical signals applied to the deaf cochlea by a cochlear implant.

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Langner, Florian, Andreas Büchner, and Waldo Nogueira. "Evaluation of an Adaptive Dynamic Compensation System in Cochlear Implant Listeners." Trends in Hearing 24 (January 2020): 233121652097034. http://dx.doi.org/10.1177/2331216520970349.

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Cochlear implant (CI) sound processing typically uses a front-end automatic gain control (AGC), reducing the acoustic dynamic range (DR) to control the output level and protect the signal processing against large amplitude changes. It can also introduce distortions into the signal and does not allow a direct mapping between acoustic input and electric output. For speech in noise, a reduction in DR can result in lower speech intelligibility due to compressed modulations of speech. This study proposes to implement a CI signal processing scheme consisting of a full acoustic DR with adaptive properties to improve the signal-to-noise ratio and overall speech intelligibility. Measurements based on the Short-Time Objective Intelligibility measure and an electrodogram analysis, as well as behavioral tests in up to 10 CI users, were used to compare performance with a single-channel, dual-loop, front-end AGC and with an adaptive back-end multiband dynamic compensation system (Voice Guard [VG]). Speech intelligibility in quiet and at a +10 dB signal-to-noise ratio was assessed with the Hochmair–Schulz–Moser sentence test. A logatome discrimination task with different consonants was performed in quiet. Speech intelligibility was significantly higher in quiet for VG than for AGC, but intelligibility was similar in noise. Participants obtained significantly better scores with VG than AGC in the logatome discrimination task. The objective measurements predicted significantly better performance estimates for VG. Overall, a dynamic compensation system can outperform a single-stage compression (AGC + linear compression) for speech perception in quiet.

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Frush Holt. "Assistive Hearing Technology for Deaf and Hard-of-Hearing Spoken Language Learners." Education Sciences 9, no. 2 (June 19, 2019): 153. http://dx.doi.org/10.3390/educsci9020153.

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Radical advancements in hearing technology in the last 30 years have offered some deaf and hard-of-hearing (DHH) children the adequate auditory access necessary to acquire spoken language with high-quality early intervention. However, meaningful achievement gaps in reading and spoken language persist despite the engineering marvel of modern hearing aids and cochlear implants. Moreover, there is enormous unexplained variability in spoken language and literacy outcomes. Aspects of signal processing in both hearing aids and cochlear implants are discussed as they relate to spoken language outcomes in preschool and school-age children. In suggesting areas for future research, a case is made for not only expanding the search for mechanisms of influence on outcomes outside of traditional device- and child-related factors, but also for framing the search within Biopsychosocial systems theories. This theoretical approach incorporates systems of risk factors across many levels, as well as the bidirectional and complex ways in which factors influence each other. The combination of sophisticated hearing technology and a fuller understanding of the complex environmental and biological factors that shape development will help maximize spoken language outcomes in DHH children and contribute to laying the groundwork for successful literacy and academic development.

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Moore, Brian C. J. "Coding of Sounds in the Auditory System and Its Relevance to Signal Processing and Coding in Cochlear Implants." Otology & Neurotology 24, no. 2 (March 2003): 243–54. http://dx.doi.org/10.1097/00129492-200303000-00019.

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Francart, Tom, and Hugh J. McDermott. "Psychophysics, Fitting, and Signal Processing for Combined Hearing Aid and Cochlear Implant Stimulation." Ear and Hearing 34, no. 6 (2013): 685–700. http://dx.doi.org/10.1097/aud.0b013e31829d14cb.

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Wolfe, Jace, Sara Neumann, Megan Marsh, Erin Schafer, Leslie Lianos, Jan Gilden, Lori O’Neill, et al. "Benefits of Adaptive Signal Processing in a Commercially Available Cochlear Implant Sound Processor." Otology & Neurotology 36, no. 7 (August 2015): 1181–90. http://dx.doi.org/10.1097/mao.0000000000000781.

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Bhatti, Pamela T., and James H. McClellan. "A Cochlear Implant Signal Processing Lab: Exploration of a Problem-Based Learning Exercise." IEEE Transactions on Education 54, no. 4 (November 2011): 628–36. http://dx.doi.org/10.1109/te.2010.2103317.

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Runge, Christina L., Kathryn Henion, Sergey Tarima, Anne Beiter, and Teresa A. Zwolan. "Clinical Outcomes of the Cochlear™ Nucleus® 5 Cochlear Implant System and SmartSound™ 2 Signal Processing." Journal of the American Academy of Audiology 27, no. 06 (June 2016): 425–40. http://dx.doi.org/10.3766/jaaa.15021.

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Background: While published data exist regarding cochlear implant (CI) outcomes from large academic programs, evidence of benefit based on national, multicenter clinical trials is needed for information regarding typical patient outcomes of devices implanted by U.S. centers representing larger academic to smaller hospital-based programs. Purpose: This nationwide trial evaluated outcomes in a group of newly implanted adult recipients of the Cochlear™ Nucleus® 5 CI system and SmartSound™ 2 signal processing. Unlike previous clinical trials, the AzBio sentence test was used and represents recent transition in our field to use of more challenging test materials. It was hypothesized that (1) speech perception scores in quiet with SmartSound™ 2 signal processing would not be statistically different from previous-generation devices; (2) speech perception scores in noise with SmartSound™ 2 signal processing would be better with enhanced microphone directionality; (3) speech perception scores in noise will be better with the preferred SmartSound™ 2 program for listening in noise; and (4) cochlear implantation would improve quality of life as assessed by the updated Health Utility Index Mark 3 (HUI3). A secondary purpose was to examine the relationships among the current and previously used speech perception tests of the Minimum Speech Test Battery (MSTB). It was hypothesized that speech perception scores within the same test interval would show predictive relationships. Research Design: Prospective, single-arm, repeated-measures study across 13 CI centers in the United States between February 2010 and June 2012. The participating centers ranged from larger academic to smaller hospital-based programs to accurately represent the diversity of programs in the United States. Study Sample: Participants were 38 postlingually deafened adult CI candidates. Data Collection and Analysis: Primary measures were Consonant-Nucleus-Consonant (CNC) words in quiet and the AzBio Sentence Test in Quiet (AzBioQ) and in Noise (AzBioN) tested at preoperative, and 3-, 6-, and 12-mo postactivation intervals. Quality of life was measured with the HUI3. For the secondary objective, statistical analyses were performed to investigate the predictive properties between current and previously used MSTB tests. Results: Mean CNC scores were significantly higher compared to the Nucleus® 24 Contour™ at 3 mo (p < 0.05) postactivation and showed no difference compared to the Nucleus® Freedom™ at 6 mo postactivation. Both SmartSound™ 2 FOCUS and NOISE programs provided significant improvements in performance in noise over the EVERYDAY program (p < 0.001), and performance with the FOCUS program was significantly better compared to the NOISE program (p < 0.001). Speech perception in noise was not related to patients’ subjective program preferences. Quality-of-life outcomes showed significant improvements from the preoperative to 6-mo postactivation interval (p < 0.05–0.001). Strong and significant correlations were found between preoperative CNC and AzBioQ and preoperative Hearing-in-Noise Test sentences in Quiet (HINTQ) and AzBioQ. At 12-mo postactivation, there were strong and highly significant correlations between CNC and AzBioQ, HINTQ and AzBioQ, and Hearing-in-Noise Test sentences in Noise and AzBioN (all p < 0.001). Conclusions: Results of this national clinical trial showed significant improvements in speech perception and quality of life following cochlear implantation. SmartSound™ 2 signal processing features showed a significant benefit of FOCUS when listening in noise, although preference of signal processing feature did not correlate with performance. Significant correlations were observed between speech perception tests. The findings of this study can be applied in clinical assessment, programming, and follow-up for CI candidates and recipients.

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Dorman, Michael F., Philipos C. Loizou, Anthony J. Spahr, and Erin Maloff. "A Comparison of the Speech Understanding Provided by Acoustic Models of Fixed-Channel and Channel-Picking Signal Processors for Cochlear Implants." Journal of Speech, Language, and Hearing Research 45, no. 4 (August 2002): 783–88. http://dx.doi.org/10.1044/1092-4388(2002/063).

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Vowels, consonants, and sentences were processed by two cochlear-implant signal-processing strategies—a fixed-channel strategy and a channel-picking strategy—and the resulting signals were presented to listeners with normal hearing for identification. At issue was the number of channels of stimulation needed in each strategy to achieve an equivalent level of speech recognition in quiet and in noise. In quiet, 8 fixed channels allowed a performance maximum for the most difficult stimulus material. A similar level of performance was reached with a 6-of-20 channel-picking strategy. In noise, 10 fixed channels allowed a performance maximum for the most difficult stimulus material. A similar level of performance was reached with a 9-of-20 strategy. Both strategies are capable of providing a very high level of speech recognition. Choosing between the two strategies may, ultimately, depend on issues that are independent of speech recognition—such as ease of device programming.

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Nittrouer, Susan, and Joanna H. Lowenstein. "Weighting of Acoustic Cues to a Manner Distinction by Children With and Without Hearing Loss." Journal of Speech, Language, and Hearing Research 58, no. 3 (June 2015): 1077–92. http://dx.doi.org/10.1044/2015_jslhr-h-14-0263.

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Purpose Children must develop optimal perceptual weighting strategies for processing speech in their first language. Hearing loss can interfere with that development, especially if cochlear implants are required. The three goals of this study were to measure, for children with and without hearing loss: (a) cue weighting for a manner distinction, (b) sensitivity to those cues, and (c) real-world communication functions. Method One hundred and seven children (43 with normal hearing [NH], 17 with hearing aids [HAs], and 47 with cochlear implants [CIs]) performed several tasks: labeling of stimuli from /bɑ/-to-/wɑ/ continua varying in formant and amplitude rise time (FRT and ART), discrimination of ART, word recognition, and phonemic awareness. Results Children with hearing loss were less attentive overall to acoustic structure than children with NH. Children with CIs, but not those with HAs, weighted FRT less and ART more than children with NH. Sensitivity could not explain cue weighting. FRT cue weighting explained significant amounts of variability in word recognition and phonemic awareness; ART cue weighting did not. Conclusion Signal degradation inhibits access to spectral structure for children with CIs, but cannot explain their delayed development of optimal weighting strategies. Auditory training could strengthen the weighting of spectral cues for children with CIs, thus aiding spoken language acquisition.

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Jeanvoine, A., C. Berger-Vachon, D. Gnansia, E. Truy, and H. Thai-Van. "F065 Improved speech perception in noise for cochlear implantees using binaural signal processing." International Journal of Pediatric Otorhinolaryngology 75 (May 2011): 95. http://dx.doi.org/10.1016/s0165-5876(11)70488-8.

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Potts, Lisa G., and Kelly A. Kolb. "Effect of Different Signal-Processing Options on Speech-in-Noise Recognition for Cochlear Implant Recipients with the Cochlear CP810 Speech Processor." Journal of the American Academy of Audiology 25, no. 04 (April 2014): 367–79. http://dx.doi.org/10.3766/jaaa.25.4.8.

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Background: Difficulty understanding speech in the presence of background noise is a common report among cochlear implant (CI) recipients. Several speech-processing options designed to improve speech recognition, especially in noise, are currently available in the Cochlear Nucleus CP810 speech processor. These include adaptive dynamic range optimization (ADRO), autosensitivity control (ASC), Beam, and Zoom. Purpose: The purpose of this study was to evaluate CI recipients’ speech-in-noise recognition to determine which currently available processing option or options resulted in best performance in a simulated restaurant environment. Research Design: Experimental study with one study group. The independent variable was speech-processing option, and the dependent variable was the reception threshold for sentences score. Study Sample: Thirty-two adult CI recipients. Intervention: Eight processing options were tested: Beam, Beam + ASC, Beam + ADRO, Beam + ASC + ADRO, Zoom, Zoom + ASC, Zoom + ADRO, and Zoom + ASC + ADRO. Data Collection and Analysis: Participants repeated Hearing in Noise Test sentences presented at a 0° azimuth, with R-Space restaurant noise presented from a 360° eight-loudspeaker array at 70 dB sound pressure level. A one-way repeated-measures analysis of variance was used to analyze differences in Beam options, Zoom options, and Beam versus Zoom options. Results: Among the Beam options, Beam + ADRO was significantly poorer than Beam only, Beam + ASC, and Beam + ASC + ADRO. A 1.6-dB difference was observed between the best (Beam only) and poorest (Beam + ADRO) options. Among the Zoom options, Zoom only and Zoom + ADRO were significantly poorer than Zoom + ASC. A 2.2-dB difference was observed between the best (Zoom + ASC) and poorest (Zoom only) options. The comparison between Beam and Zoom options showed one significant difference, with Zoom only significantly poorer than Beam only. No significant difference was found between the other Beam and Zoom options (Beam + ASC vs Zoom + ASC, Beam + ADRO vs Zoom + ADRO, and Beam + ASC + ADRO vs Zoom + ASC + ADRO). The best processing option varied across subjects, with an almost equal number of participants performing best with a Beam option (n = 15) compared with a Zoom option (n = 17). There were no significant demographic or audiological moderating variables for any option. Conclusions: The results showed no significant differences between adaptive directionality (Beam) and fixed directionality (Zoom) when ASC was active in the R-Space environment. This finding suggests that noise-reduction processing is extremely valuable in loud semidiffuse environments in which the effectiveness of directional filtering might be diminished. However, there was no significant difference between the Beam-only and Beam + ASC options, which is most likely related to the additional noise cancellation performed by the Beam option (i.e., two-stage directional filtering and noise cancellation). In addition, the processing options with ADRO resulted in the poorest performances. This could be related to how the CI recipients were programmed or the loud noise level used in this study. The best processing option varied across subjects, but the majority performed best with directional filtering (Beam or Zoom) in combination with ASC. Therefore in a loud semidiffuse environment, the use of either Beam + ASC or Zoom + ASC is recommended.

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Chouard, C. H., P. MacLeod, and J. P. Weber. "Signal Processing and Psychological Considerations for the French 12-Channel Cochlear Implant (Chorimac 12)." Annals of Otology, Rhinology & Laryngology 96, no. 1_suppl (January 1987): 65. http://dx.doi.org/10.1177/00034894870960s131.

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O’Niel, Mallory B., David R. Friedland, and Christina Runge. "The Effects of Cochlear Implant Signal Processing on Discrimination of Musical Instrument Harmonic Changes." Otolaryngology–Head and Neck Surgery 151, no. 1_suppl (September 2014): P204. http://dx.doi.org/10.1177/0194599814541629a211.

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Biever, Allison, Jan Gilden, Teresa Zwolan, Megan Mears, and Anne Beiter. "Upgrade to Nucleus® 6 in Previous Generation Cochlear™ Sound Processor Recipients." Journal of the American Academy of Audiology 29, no. 09 (October 2018): 802–13. http://dx.doi.org/10.3766/jaaa.17016.

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AbstractThe Nucleus® 6 sound processor is now compatible with the Nucleus® 22 (CI22M)—Cochlear’s first generation cochlear implant. The Nucleus 6 offers three new signal processing algorithms that purportedly facilitate improved hearing in background noise.These studies were designed to evaluate listening performance and user satisfaction with the Nucleus 6 sound processor.The research design was a prospective, single-participant, repeated measures designA group of 80 participants implanted with various Nucleus internal implant devices (CI22M, CI24M, Freedom® CI24RE, CI422, and CI512) were recruited from a total of six North American sites.Participants had their external sound processor upgraded to the Nucleus 6 sound processor. Final speech perception testing in noise and subjective questionnaires were completed after four or 12 weeks of take-home use with the Nucleus 6.Speech perception testing in noise showed significant improvement and participants reported increased satisfaction with the Nucleus 6.These studies demonstrated the benefit of the new algorithms in the Nucleus 6 over previous generations of sound processors.

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Cudahy, E., D. Beck, J. Danhauer, M. Danley, P. Mobley, and M. Pratarelli. "Strategies for Optimizing the Single-Channel Cochlear Implant: Preliminary Data." Annals of Otology, Rhinology & Laryngology 96, no. 1_suppl (January 1987): 134–36. http://dx.doi.org/10.1177/00034894870960s172.

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Perception of consonants for the House 3M single-channel cochlear implant using a two-channel signal processing model was investigated. The input signal was split into a low frequency band and a high frequency band with the cutoff frequencies of the bands adjusted in nine conditions. The conditions ranged from overlapping bands that yielded a flat spectrum to bands that removed a considerable portion of the midrange frequencies. The stimuli for this study were 60-item vowel-consonant-vowel lists with male and female talkers that were presented through direct electrical connection to the implant wearer. The stimuli were recorded on tape in quiet and noise backgrounds to measure interactions among speaker gender, background, and filtering scheme. The four patients in this study were experienced implant wearers. The results were analyzed both in terms of percent correct consonant and in terms of percent correct consonant category. Three of the filter conditions show better performance than the patient's own processor. Interestingly, the best conditions have large portions of the midfrequency regions attenuated.

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Journal articles on the topic 'Signal processing. Cochlear implants'

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