This paper is in the following e-collection/theme issue:

Artificial Intelligence (1770) New Methods (1035) Clinical Information and Decision Making (1685) ENT (Ear, Nose, Throat) (32) Home Care (198) Machine Learning (1766) Disabilities (139) Consumer Health Informatics Innovations (17)

Published on in Vol 23, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25460, first published .
Improved Environment-Aware–Based Noise Reduction System for Cochlear Implant Users Based on a Knowledge Transfer Approach: Development and Usability Study

Improved Environment-Aware–Based Noise Reduction System for Cochlear Implant Users Based on a Knowledge Transfer Approach: Development and Usability Study

Improved Environment-Aware–Based Noise Reduction System for Cochlear Implant Users Based on a Knowledge Transfer Approach: Development and Usability Study

Authors of this article:

Lieber Po-Hung Li1, 2, 3, 4 Author Orcid Image ;   Ji-Yan Han5 Author Orcid Image ;   Wei-Zhong Zheng5 Author Orcid Image ;   Ren-Jie Huang5 Author Orcid Image ;   Ying-Hui Lai5 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Healy E, Johnson E, Pandey A, Wang D. Progress made in the efficacy and viability of deep-learning-based noise reduction. The Journal of the Acoustical Society of America 2023;153(5):2751 View
  2. Han J, Wang C, Li J, Lai Y. Ambulatory Phonation Monitoring Using Wireless Headphones With Deep Learning Technology. IEEE Systems Journal 2023;17(3):4752 View
  3. Chang Y, Han J, Chu W, Li L, Lai Y. Enhancing music recognition using deep learning-powered source separation technology for cochlear implant users. The Journal of the Acoustical Society of America 2024;155(3):1694 View
  4. Essaid B, Kheddar H, Batel N, Chowdhury M, Lakas A. Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives. IEEE Access 2024;12:119015 View
  5. Frosolini A, Franz L, Caragli V, Genovese E, de Filippis C, Marioni G. Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions. Sensors 2024;24(22):7126 View

Conference Proceedings

  1. Han J, Li J, Yang C, Chen F, Liao W, Liao Y, Lai Y. 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Leveraging Deep Learning to Enhance Optical Microphone System Performance with Unknown Speakers for Cochlear Implants View