Manual operation of hearing assistive devices is cumbersome in various situations. With advances in machine learning and speech technology, voice interfaces due to their convenience will be widely deployed for hearing assistive devices and they can be personalized and offer richer functionalities. Hearing assistive devices are characterized by strict memory and computational complexity constraints and the fact that they are expected to operate flawlessly, even in acoustically challenging situations. This PhD project aims to develop personalized, noise-robust and low-resource voice control systems for hearing assistive devices, using microphone signals and other modalities.
For more details, please refer to http://www.stillinger.aau.dk/vis-stilling/?vacancy=936714.
