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

  • Fergal Henry
  • , Martin Glavin
  • , Edward Jones
    • National University of Ireland, Galway

    Research output: Contribution to journalReview articlepeer-review

    30 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)

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