Cochlear implants (CI) have significantly changed the lives of hundreds of thousands hearing impaired people who could not use hearing aids effectively. However, the sound quality of the cochlear implant today is still limited in the performance of tonal languages, speech in noisy conditions and music perception. This project is going to integrate three auditory physiology based sound processing methods into an existing CI simulation platform developed by our research team and investigate the Mandarin speech recognition performance of these methods with the ACE (advanced combination encoder) strategy under various combinations. The sound processing methods, developed from auditory processing mechanisms absent in CI users, involves a biologically inspired hearing aid (BioAid) algorithm models the instantaneous compression of the basilar membrane, the envelope enhancement (EE) strategy simulates the olivocochlear (MOC) reflex, and the F0 modulation (F0mod) strategy, which preserves the periodicity pitch required by auditory perception. In the first year of this project, sound processing methods are going to be implemented to the experiment platform, which will be used for CI stimulations with multiple combinations of processing methods and noisy conditions. In clinical experiments of the second year, the experiment platform will be expanded with hardware control functionality, which directly streams processed signals into a CI recipient’s internal implant via the NIC (Nucleus implant communicator) and a research processor. Hence the actual electric stimulation results can be evaluated. Based on the outcomes of simulations and clinical experiments, Mandarin lexical tone identification and speech recognition in noise affected by different combinations of sound processing methods are going to be compared in order to bring positive effects on related studies in the field of cochlear implant sound processing.
|Effective start/end date||1/08/18 → 31/07/19|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):