Machine learning applications for hearing and hearing technology

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We are interested in applying the principles of machine learning and big data to problems in the hearing space.  We hold regular meetings with a design thinking approach with a goal of grant applications and the production of intellectual property. Group members come from the Australian Hearing Hub and have backgrounds in psychoacoustics, engineering, physics, statistics, automatic speech recognition, signal processing, and natural language processing

Upcoming events: Australian Hearing Hub Hackathon



Project Leads:  Dr Jessica Monaghan and Dr Jorge Mejia

Dr Jessica Monaghan Jess Monaghan
Research Fellow, Macquarie University
Jessica Monaghan started her scientific career reading Natural Sciences at the University of Cambridge, specialising in Physics. There she completely her Masters research project into how the principles of human listening might be applied to improve automatic speech recognition by machines at the Centre for the Neural Basis of Hearing (CNBH). After working at the CNBH for a year as a research assistant, she undertook her PhD studies at the UK Medical Research Council’s Institute for Hearing Research, where she developed an algorithm to improve the ability of cochlear implant users to localise sounds in rooms. As a postdoctoral researcher at the University of Southampton, she developed noise-reduction algorithms for hearing aids and cochlear implants using state-of-the-art machine learning techniques such as deep neural networks and sparse coding. In 2015 she moved to Australia to work as a Research Fellow at Macquarie University, where she is researching the ability of people with normal hearing to understand speech in noisy environments, and using this knowledge to develop the next generation of hearing devices.

Jorge MejiaDr Jorge Mejia
Head of signal processing, National Acoustic Laboratories
Dr Jorge Mejia completed a BEng and Computer Science degree from the Queensland University of Technology in 1999. He continued his post-graduate studies and completed a Diploma in Control Engineering, and subsequently a Masters in Computer Science in 2003, graduating with high honours.From 2000 to 2004 Jorge worked with industry in the area of hearing aid research and development. Since 2004 he joined the National Acoustic Laboratories (NAL) and became involved in the area of binaural hearing research. Since 2018, Jorge leads the signal processing department at NAL.

His research is focused on the psycho-acoustics of hearing and signal processing coding for hearing devices including hearable, hearing aids, cochlear implants and assistive listening technologies.