With the rise of speech and audio-steered automatic systems, their limitations have become apparent as well: automatic speech recognition fails when acoustic conditions are sub-optimal, and consumer electronics are not tailored to the hearing pathologies of individuals interfacing with them. This line of research focusses on the development of bio-inspired audioapplications that benefit from the remarkable properties of human hearing. They are personalised such that they can compensate for an individuals’ hearing pathology and thereby improve user experience. The project connects the neuroscience of hearing (damage), computational auditory modelling with the latest machine-learning techniques to innovate within this domain.