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Noise Reduction in Cochlear Implant Signal Processing: A Review and Recent Developments.
IEEE Reviews in Biomedical Engineering
|July 7, 2021
Summary
Cochlear implants improve hearing but struggle in noise. This review examines noise reduction algorithms for cochlear implant technology, including traditional and machine learning methods, to enhance user experience in challenging sound environments.
Area of Science:
- Audiology and Biomedical Engineering
- Signal Processing
Background:
- Cochlear implant technology restores hearing but faces challenges in noisy environments.
- Effective noise reduction is crucial for improving cochlear implant user experience.
Approach:
- This paper reviews noise reduction algorithms for cochlear implants.
- Algorithms are classified as single- or multiple-channel, incorporating recent machine learning advancements.
- The review analyzes recent research papers on these techniques.
Key Points:
- Traditional noise reduction algorithms are categorized by microphone usage (single- vs. multiple-channel).
- Machine learning techniques are increasingly integrated into cochlear implant noise reduction.
- Current algorithms aim to improve speech intelligibility and listening comfort in adverse acoustic conditions.
Conclusions:
- Noise reduction remains a critical area for cochlear implant development.
- Future research should focus on advanced signal processing and adaptive algorithms.
- Machine learning offers promising avenues for next-generation cochlear implant noise reduction.
