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Single and multiple microphone noise reduction strategies in cochlear implants. Trends Amplif 2012 Jun;16(2):102-16



Pubmed ID


Pubmed Central ID




Scopus ID

2-s2.0-84867357313   41 Citations


To restore hearing sensation, cochlear implants deliver electrical pulses to the auditory nerve by relying on sophisticated signal processing algorithms that convert acoustic inputs to electrical stimuli. Although individuals fitted with cochlear implants perform well in quiet, in the presence of background noise, the speech intelligibility of cochlear implant listeners is more susceptible to background noise than that of normal hearing listeners. Traditionally, to increase performance in noise, single-microphone noise reduction strategies have been used. More recently, a number of approaches have suggested that speech intelligibility in noise can be improved further by making use of two or more microphones, instead. Processing strategies based on multiple microphones can better exploit the spatial diversity of speech and noise because such strategies rely mostly on spatial information about the relative position of competing sound sources. In this article, we identify and elucidate the most significant theoretical aspects that underpin single- and multi-microphone noise reduction strategies for cochlear implants. More analytically, we focus on strategies of both types that have been shown to be promising for use in current-generation implant devices. We present data from past and more recent studies, and furthermore we outline the direction that future research in the area of noise reduction for cochlear implants could follow.

Author List

Kokkinakis K, Azimi B, Hu Y, Friedland DR


David R. Friedland MD Associate Director, Director, Chief, Professor in the Otolaryngology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Cochlear Implantation
Cochlear Implants
Correction of Hearing Impairment
Perceptual Masking
Persons With Hearing Impairments
Prosthesis Design
Signal Processing, Computer-Assisted
Speech Intelligibility
Speech Perception