AI-Based Fine-Tuning: How Signia Assistant Improves Wearer Acceptance Rates
Course: #38586Level: Intermediate 2 Hours 346 Reviews
Despite major advances in all steps of the hearing aid fitting process, fine-tuning to arrive at the correct settings is still, and likely will remain, a key part of the wearer’s initial experience. This article demonstrates how an AI-driven, self-guided fine-tuning app--one that improves over time as more wearer data is entered into the system--drives better outcomes.
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Learning Outcomes
- After this course, participants will be able to describe the overall concept of the Signia Assistant.
- After this course, participants will be able to describe the benefits of an artificial intelligence-enabled personal assistant for hearing aid wearers and hearing care professionals.
- After this course, participants will be able to explain some of the reasons an artificial intelligence (AI) assistant with a deep neural network (DNN) can improve its performance over time.
Course created on April 3, 2023
Reviews
346 ReviewsPresented By
Niels Søgaard Jensen
MSc
Senior Evidence and Research Specialist, WSA Audiology
Niels Søgaard Jensen received his M.Sc. degree in acoustics and psychoacoustics from the Technical University of Denmark. He has a background as research engineer in the hearing aid industry where he has done research on various topics related to hearing loss and hearing aids. In 2016 he joined WS Audiology where he holds a position as Senior Evidence and Research Specialist in Lynge, Denmark.
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Brian Taylor
AuD
Brian Taylor is a Doctor of Audiology and Senior Director of Audiology for Signia. He is also the editor of Audiology Practices, a quarterly journal of the Academy of Doctors of Audiology, editor-at-large for Hearing Health and Technology Matters and adjunct instructor at the University of Wisconsin. Dr. Taylor has authored several peer reviewed articles and textbooks and is a highly sought out lecturer. Brian has nearly 30 years of experience as both a clinician, business manager and university instructor.
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Michael Müller
PhD
Michael Müller received his MSc in Information and Computer Engineering and a PhD in Computational Neuroscience from Graz University of Technology. He joined WS Audiology in 2022, where he uses his background in signal processing, machine learning, and data analysis for the development of data-driven methods for improving hearing aids such as the Signia Assistant.
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Financial: Brian Taylor is an employee of WS Audiology. Non-financial: Brian Taylor has no relevant non-financial relationships to disclose.
Financial: Michael Müller is an employee of WS Audiology. Non-financial: Michael Müller has no relevant non-financial relationships to disclose.
Sponsor Disclosure: This Course is presented by Signia in partnership with AudiologyOnline.
Content Disclosure: This learning event focuses on Signia products and services and will not include info on other products or services.
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American Academy of Audiology
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Australian College of Audiology
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Association of Hearing Instrument Practitioners of Ontario
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American Speech-Language-Hearing Assn.
Intermediate Level
0.2 ASHA CEUs
British Academy of Audiology
This course has been accredited with 2 CPD point/s by the British Academy of Audiology.
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International Hearing Society
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Kansas Department for Aging and Disability Services
Kansas Department of Health and Environment: Approved for 2 continuing education clock hours for Kansas licensed Audiologists by the Kansas Department for Aging and Disability Services. Long-Term Sponsorship number LTS-S0035.
New Zealand Audiological Society
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