journal article·2019-02-20Open access

Hearing in Noise: The Importance of Coding Strategies—Normal-Hearing Subjects and Cochlear Implant Users

Pierre-Antoine Cucis, Christian Berger-Vachon, Ruben Hermann, Fabien Millioz, Eric Truy, Stéphane Gallego

Applied Sciences· Volume 9· Issue 4

Abstract

Two schemes are mainly used for coding sounds in cochlear implants: Fixed-Channel and Channel-Picking. This study aims to determine the speech audiometry scores in noise of people using either type of sound coding scheme. Twenty normal-hearing and 45 cochlear implant subjects participated in this experiment. Both populations were tested by using dissyllabic words mixed with cocktail-party noise. A cochlear implant simulator was used to test the normal-hearing subjects. This simulator separated the sound into 20 spectral channels and the eight most energetic were selected to simulate the Channel-Picking strategy. For normal-hearing subjects, we noticed higher scores with the Fixed-Channel strategy than with the Channel-Picking strategy in the mid-range signal-to-noise ratios (0 to +6 dB). For cochlear implant users, no differences were found between the two coding schemes but we could see a slight advantage for the Fixed-Channel strategies over the Channel-Picking strategies. For both populations, a difference was observed for the signal-to-noise ratios at 50% of the maximum recognition plateau in favour of the Fixed-Channel strategy. To conclude, in the most common signal-to-noise ratio conditions, a Fixed-Channel coding strategy may lead to better recognition percentages than a Channel-Picking strategy. Further studies are indicated to confirm this.
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Research context

OpenAlex topics: Hearing Loss and Rehabilitation · Speech and Audio Processing · Noise Effects and Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Integrative, Multisensory, Perception, Action and Cognition Team (IMPACT), INSERM U1028, CNRS UMR 5292, Claude-Bernard Lyon1 University, 69676 Bron, France

ENT and Cervico-Facial Surgery Department, Edouard Herriot Hospital, 69003 Lyon, France

Brain Dynamics and Cognition (DYCOG), INSERM U1028, CNRS UMR 5292, Claude-Bernard Lyon1 University, 69676 Bron CEDEX, France

Biomechanics and Impact Mechanics Laboratory (LBMC), French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR), CNRS UMR T9406, Claude-Bernard Lyon1 University, 69675 Bron CEDEX, France

Centre for Research into the Acquisition and Processing of Images for Healthcare (CREATIS), INSERM U1206, CNRS UMR5220, INSA, Claude-Bernard Lyon1 University, F69621 Lyon, France

Sensory and Cognitive Neuroscience Laboratory (LNSC), CNRS UMR 7260, Aix-Marseille University, 13331 Marseille, France

Institute of Rehabilitation Sciences and Techniques (ISTR), Claude-Bernard Lyon1 University, 69373 Lyon CEDEX 08, France

References (39)

Show source-provided references
1. (2017, June 14). NIDCD, Available online: https://www.nidcd.nih.gov/.
2. Speech recognition in background noise of cochlear implant patients10.1067/mhn.2002.123044 ↗
3. Clark, G. (2006). Cochlear Implants: Fundamentals and Applications, Springer Science & Business Media.
4. Factors affecting auditory performance of postlinguistically deaf adults using cochlear implants: An update with 2251 patients10.1159/000343189 ↗
5. Speech understanding in quiet and in noise with the CIS speech coding strategy (MED-EL Combi-40) compared to the multipeak and spectral peak strategies (nucleus)10.1159/000276812 ↗
6. Comparison of speech recognition with different speech coding strategies (SPEAK, CIS and ACE) and their relationship to telemetric measures of compound action potentials in the nucleus CI 24M cochlear implant system10.3109/00206090109073098 ↗
7. Speech recognition with the nucleus 24 SPEAK, ACE and CIS speech coding strategies in newly implanted adults10.1097/00003446-200206000-00005 ↗
8. Comparison of musical activities of cochlear implant users with different speech-coding strategies10.1097/AUD.0b013e3180315468 ↗
9. A comparison of the speech understanding provided by acoustic models of fixed-channel and channel-picking signal processors for cochlear implants10.1044/1092-4388(2002/063) ↗
10. The number of spectral channels required for speech recognition depends on the difficulty of the listening situation10.1080/03655230410017562 ↗
11. Effect of stimulation rate on speech perception in adult users of the Med-El CIS speech processing strategy10.1080/14992020400022488 ↗
12. Better speech recognition with cochlear implants10.1038/352236a0 ↗
13. Understanding the effect of noise on electrical stimulation sequences in cochlear implants and its impact on speech intelligibility10.1016/j.heares.2013.01.018 ↗
14. Speech understanding in noise with a Med-El COMBI 40+ cochlear implant using reduced channel sets10.1097/00003446-200212000-00005 ↗
15. A new sound coding strategy for suppressing noise in cochlear implants10.1121/1.2924131 ↗
16. Jeanvoine, A., Gnansia, D., Truy, E., and Berger-Vachon, C. (2015). Contribution of Noise Reduction Algorithms: Perception Versus Localization Simulation in the Case of Binaural Cochlear Implant (BCI) Coding. Emerging Trends in Computational Biology, Bioinformatics and System Biology, Elsevier Inc.10.1016/B978-0-12-802508-6.00016-8 ↗
17. Wang, Q., Liang, R., Rahardja, S., Zhao, L., Zou, C., and Zhao, L. (2017). Piecewise-Linear Frequency Shifting Algorithm for Frequency Resolution Enhancement in Digital Hearing Aids. Appl. Sci., 7.10.3390/app7040335 ↗
18. Dual-channel spectral subtraction algorithms based speech enhancement dedicated to a bilateral cochlear implant10.1016/j.apacoust.2011.06.010 ↗
19. Influence of coding strategies in electric-acoustic hearing: A simulation dedicated to EAS cochlear implant, in the presence of noise10.1016/j.apacoust.2013.08.003 ↗
20. Recognition of monosyllabic words by cochlear implant patients and by normal-hearing subjects listening to words processed through cochlear implant signal processing strategies10.1177/0003489400109S1227 ↗
21. Recognition of sentences in noise by normal-hearing listeners using simulations of speak-type cochlear implant signal processors10.1177/0003489400109S1228 ↗
22. The identification of speech in noise by cochlear implant patients and normal-hearing listeners using 6-channel signal processors10.1097/00003446-199812000-00009 ↗
23. The use of auditory and visual context in speech perception by listeners with normal hearing and listeners with cochlear implants10.3389/fpsyg.2013.00824 ↗
24. Influence of Microphone Encrusting on the Efficiency of Cochlear Implants Preliminary Study with a Simulation of CIS and “n-of-m” Strategies
25. Subcortical Laterality of Speech Encoding10.1159/000188533 ↗
26. Structure and function of auditory cortex: Music and speech10.1016/S1364-6613(00)01816-7 ↗
27. Analytical expressions for the tonotopic sensory scale10.1121/1.399849 ↗
28. Sound Coding in Cochlear Implants: From electric pulses to hearing10.1109/MSP.2014.2371671 ↗
29. Using Effect Size—Or Why the P Value Is Not Enough10.4300/JGME-D-12-00156.1 ↗
30. When to use the Bonferroni correction10.1111/opo.12131 ↗
31. Correction for multiple testing: Is there a resolution?10.1378/chest.11-0523 ↗
32. Nucleus 24 advanced encoder conversion study: Performance versus preference10.1097/00003446-200202001-00002 ↗
33. Influence of a shift in frequency distribution and analysis rate on phoneme intelligibility in noisy environments for simulated bilateral cochlear implants10.1016/j.apacoust.2012.05.014 ↗
34. Effects of stimulation rate with the fs4 and hdcis coding strategies in cochlear implant recipients10.1097/MAO.0000000000001107 ↗
35. Representation of fine structure or fine frequency information with cochlear implants10.1016/j.ics.2004.08.018 ↗
36. The identification of consonants and vowels by cochlear implant patients using a 6-channel continuous interleaved sampling processor and by normal-hearing subjects using simulations of processors with two to nine channels10.1097/00003446-199804000-00008 ↗
37. Information theoretic evaluation of a noiseband-based cochlear implant simulator10.1016/j.heares.2015.09.008 ↗
38. Speech recognition in noise as a function of the number of spectral channels: Comparison of acoustic hearing and cochlear implants10.1121/1.1381538 ↗
39. On the number of channels needed to understand speech10.1121/1.427954 ↗