Current Issue
Volumes and Issues
For Authors
Manuscript Guidelines
Review Process
Conflict of Interest
Copyright
About the Journal
Editorial Board
Aim and Scope
Policy and Ethical Guidelines
Promotion of the Journal
Print-Version Subscription
Publisher and Contact Information
Contact Information
Sign in
REVIEW PAPER
APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN HEARING AIDS AND AUDITORY IMPLANTS: A SHORT REVIEW
1
Audiology, All India Institute of Speech and Hearing, India
2
Audiology, MERF Institute of Speech and Hearing (p) Ltd, India
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article;
Publication date: 2021-12-03
Corresponding author
Pachaiappan C
Audiology, MERF Institute of Speech and Hearing (p) Ltd, Old No. 1/1, 600028, Chennai, India
Audiology, MERF Institute of Speech and Hearing (p) Ltd, Old No. 1/1, 600028, Chennai, India
J Hear Sci 2021;11(3):20-23
KEYWORDS
TOPICS
ABSTRACT
Artificial intelligence (AI) has been broadly used for a long time, but in terms of hearing aids it only came into the limelight in 2004. Although at that time AI was yet to be incorporated into a hearing aid, with improvement in technology, slowly AI began to be introduced. AI included trainable hearing aids, own voice processing, brain-controlled hearing aids, strategies to improve speech perception in noise, and wind noise management in both hearing aids and cochlear implants. This short review discusses these AI technologies and their utility for the user.
REFERENCES (33)
1.
Copeland J. Artificial Intelligence: A philosophical introduction. John Wiley & Sons, 2015.
2.
Copeland BJ, Proudfoot D. Artificial intelligence: history, foundations, and philosophical issues. In: Philosophy of Psychology and Cognitive Science, North-Holland, 2007, pp.429–82.
3.
Saleh Z. Artificial Intelligence: Definition, ethics and standards. The British University in Egypt, Cairo, 2019.
4.
Schum DJ. Artificial intelligence: the new advanced technology in hearing aids. Audiology Online, 2004:14-06.
5.
Aliabadi M, Farhadian M, Darvishi E. Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach. Int Arch Occupat Env Health, 2015 Aug 1; 88(6): 779–87.
6.
Wolfgang K. Artificial intelligence and machine learning: pushing new boundaries in hearing technology. Hear J, 2019 Mar 1; 72(3): 26–7.
7.
Park G, Cho W, Kim K-S, Lee, S. Speech enhancement for hearing aids with deep learning on environmental noises. Appl Sciences, 2020; 10: 6077.
8.
Lee YC, Chi TS, Yang CH. A 2.17mW acoustic DSP processor with CNN-FFT accelerators for intelligent hearing aided devices. IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) 2019 Mar 18, pp. 97–101.
9.
Townend O, Nielsen JB, Ramsgaard J. Real-life applications of machine learning in hearing aids. Hear Rev, 2018; 25(4): 34–7.
10.
Zhang T, Mustiere F, Micheyl C. Intelligent hearing aids: the next revolution. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016 Aug 16, pp.72–6.
11.
How machine learning revolutionizes hearing aids. Signia Hearing Aids, 2019. Available from: https://www.signia-hearing.com....
12.
Conde T, Gonçalves ÓF, Pinheiro AP. Stimulus complexity matters when you hear your own voice: attention effects on self-generated voice processing. Int J Psychophysiol, 2018 Nov 1; 133: 66–78.
13.
Mesgarani N. Brain-controlled hearing aids for better speech perception in noisy settings. Hear J, 2019 Sep 1; 72(9): 10–2.
14.
Flynn MC, Lunner T. Clinical verification of a hearing aid with artificial intelligence. Hear J, 2005 Feb 1; 58(2): 34–8.
15.
Townend O, Nielsen JB, Balslev D. SoundSense Learn: Listening intention and machine learning. Hear Rev, 2018; 25(6): 28–31.
17.
Starkey Hearing. Welcome to the leading edge of hearing technology. Available from: https://www.starkey.com/blog/a....
18.
Flynn, MC. Maximizing the voice-to-noise ratio (VNR) via voice priority processing. Hear Rev, 2004 Apr 8; 11(4), 54–9.
19.
Xu Y, Du J, Dai LR, Lee CH. A regression approach to speech enhancement based on deep neural networks. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2014 Oct 21; 23(1): 7–19.
20.
Crowson MG, Lin V, Chen JM, Chan TC. Machine learning and cochlear implantation: a structured review of opportunities and challenges. Otol Neurotol, 2020 Jan 1; 41(1): e36–45.
21.
Van Dijk B, Botros AM, Battmer R-D, et al. Clinical results of AutoNRT, a completely automatic ECAP recording system for cochlear implants. Ear Hear 2007; 28: 558–70.
22.
Feng G, Ingvalson EM, Grieco-Calub TM, et al. Neural preservation underlies speech improvement from auditory deprivation in young cochlear implant recipients. Proc Natl Acad Sci U S A, 2018; 115: 1022–31.
23.
Tan L, Holland SK, Deshpande AK, Chen Y, Choo DI, Lu LJ. A semi-supervised support vector machine model for predicting the language outcomes following cochlear implantation based on preimplant brain fMRI imaging. Brain Behav, 2015; 5: 1–25.
24.
Kim H, Kang WS, Park HJ, Lee JY, Park JW, Kim Y, Seo JW, Kwak MY, Kang BC, Yang CJ, Duffy BA. Cochlear implantation in postlingually deaf adults is time-sensitive towards positive outcome: prediction using advanced machine learning techniques. Scientific Reports, 2018 Dec 20; 8(1): 1–9.
26.
Ashburn-Reed S. Cochlear unveils Kanso™, a first-of-its-kind hearing technology to treat severe to profound hearing loss. 2016 Sep 16. Available from: https://pronews.cochlearameric....
27.
Warren C, Nel E, Kwok B. Nucleus 7 moves forward: a new noise reduction algorithm. J Hear Sci, 2018; 8(2): 91–2.
29.
Hazama M, Sasaki M, Nakahara K, Hojo T, Sakoda T, Kawano A. Efficacy of speech in noise using Naida Q90 CI, benefit of speech perception in noise with the latest noise reduction algorithm. J Hear Sci, 2018 Jun 1; 8(2): 174.
30.
Warren CD, Nel E, Boyd PJ. Controlled comparative clinical trial of hearing benefit outcomes for users of the Cochlear™ Nucleus® 7 Sound Processor with mobile connectivity. Cochlear Implants Intl, 2019 May 4; 20(3): 116–26.
31.
Musk E. An integrated brain–machine interface platform with thousands of channels. J Medical Internet Research, 2019; 21(10): e16194.
32.
Kulshreshth A, Anand A, Lakanpal A. Neuralink: an Elon Musk start-up achieve symbiosis with artificial intelligence. International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), 2019 Oct 18, pp. 105–9.
33.
Umashankar A, Prabhu P. Can Neuralink be effective for bionic hearing? [online blog] Hear J, 2020; 73(12).
Share
RELATED ARTICLE
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
