Assessing cognitive load in cochlear implant users through short-term storage of speech

Cochlear implants are surgical implanted devices that allow deaf people to recover some form of hearing and understand speech, but current devices are limited, and the consequences of these limitations have not been fully explored. For example, there is a growing consensus that hearing loss interacts with cognitive systems. Yet, relatively little is known about the cognitive burden of CI users. The present project will develop a robust tool to measure the cognitive effort induced by the CI, and point towards the poor representation of voice pitch as one important cause for the increased listening effort and the reduced short-term memory. We eventually aim to develop a pitch-exaggeration algorithm in pseudo-real-time, which could be implemented by the partnering industry Oticon in the design of future CI processors.

Intern: 
Yue Zhang
Faculty Supervisor: 
Alexandre Lehmann
Province: 
Quebec
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