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Grant: Discovery Grants Program - Individual

Université d'Ottawa

$40,000.00

Deep learning advances for signal processing tasks in hearing aids

FY 2024-25

Summary
The research program in this Discovery grant proposal aims to develop innovative and efficient deep learning solutions for signal processing tasks required in hearing aid devices. Hearing loss is a severe problem affecting many Canadians and hearing aids are an efficient way of at least partially compensating for several types of hearing loss. Quality-of-life benefits for hearing aid owners have increased over the last decade, but recent surveys indicate that further developments are still required. Deep learning methods have recently shown good potential to provide significant improvements for some of the signal processing tasks required in hearing aids (e.g., sources detection, noise suppression, acoustic feedback canceling), but the complexity of the best performing methods is still too large for practical use in hearing aids. To achieve tangible progress in the proposed research program, this proposal includes both strategies to reduce the complexity of deep learning systems suitable for hearing aids signal processing tasks and directions to develop better-performing deep learning systems for the tasks. This Discovery grant will train HQP in the highly in-demand field of machine learning for signal processing, with clear economic and healthcare benefits to Canada.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2024-04187
Name nom
Bouchard, Martin
Department département
School of Electrical Engineering and Computer Science
Organization id
28
Institution établissement
Université d'Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
40000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
518
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Medical equipment and apparatus
Area of application fr
Appareils et instruments médicaux
Research subject code
2514
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Digital signal processing
Research subject fr
Traitement des signaux numériques
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Deep learning advances for signal processing tasks in hearing aids
Keywords
hearing aids signal processing; noise suppression in speech signals; acoustic feedback cancellation; acoustic sources direction of arrival estimation; deep learning; complexity reduction in deep learning models
Application summary
The research program in this Discovery grant proposal aims to develop innovative and efficient deep learning solutions for signal processing tasks required in hearing aid devices. Hearing loss is a severe problem affecting many Canadians and hearing aids are an efficient way of at least partially compensating for several types of hearing loss. Quality-of-life benefits for hearing aid owners have increased over the last decade, but recent surveys indicate that further developments are still required. Deep learning methods have recently shown good potential to provide significant improvements for some of the signal processing tasks required in hearing aids (e.g., sources detection, noise suppression, acoustic feedback canceling), but the complexity of the best performing methods is still too large for practical use in hearing aids. To achieve tangible progress in the proposed research program, this proposal includes both strategies to reduce the complexity of deep learning systems suitable for hearing aids signal processing tasks and directions to develop better-performing deep learning systems for the tasks. This Discovery grant will train HQP in the highly in-demand field of machine learning for signal processing, with clear economic and healthcare benefits to Canada.