Noise Reduction in Cochlear Implant Signal Processing: A Review and Recent Developments

Fergal Henry, Martin Glavin, Edward Jones

Research output: Contribution to journalReview articlepeer-review

8 Citations (Scopus)

Abstract

Cochlear implant technology successfully restores hearing function to patients with sensory impairment. Although cochlear implant users generally hear well in quiet, they still find noisy conditions very challenging, hence the need to employ noise reduction algorithms in these systems to enhance the user experience. This paper reviews noise reduction algorithms in cochlear implants. Traditionally, such algorithms have been classified as either single- or multiple-channel, depending on the number of microphones they use. This review retains this general classification in looking at recent papers and extends it to reflect recent interest in machine learning techniques. The review concludes with consideration of promising future areas of research.

Original languageEnglish
Pages (from-to)319-331
Number of pages13
JournalIEEE Reviews in Biomedical Engineering
Volume16
DOIs
Publication statusPublished - 2023

Keywords

  • Cochlear implant (CI)
  • deep neural networks (DNNs)
  • hearing aid (HA)
  • hearing impaired (HI)
  • machine learning (ML)
  • neural networks (NNs)
  • noise reduction (NR)
  • normal hearing (NH)
  • speech distortion (SD)
  • speech intelligibility (SI)
  • speech quality (SQ)
  • speech/sound processor (SP)

Fingerprint

Dive into the research topics of 'Noise Reduction in Cochlear Implant Signal Processing: A Review and Recent Developments'. Together they form a unique fingerprint.

Cite this