Manual operation of hearing assistive devices is cumbersome in various situations. With advances in machine learning and speech technology, voice interfaces are being deployed for hearing assistive devices. Hearing assistive devices are characterized by strict memory and computational complexity constraints and by the fact that they are expected to operate flawlessly, even in acoustically challenging situations. This PhD project aims to develop personalized, noise-robust and super low-resource voice control systems for hearing assistive devices, using microphone signals and other modalities.
The project will be conducted at the newly founded Centre for Acoustic Signal Processing Research (CASPR, http://caspr.es.aau.dk/ ) of the Section for Signal and Information Processing, Department of Electronic Systems, Aalborg University. The Centre focuses on conducting research and education in scientific disciplines supporting future statistical signal processing concepts for hearing assistive devices.
The successful applicant must have a Master degree in machine learning, statistical signal processing, speech processing or acoustic signal processing, and have extensive knowledge in one or more of these disciplines. Excellent undergraduate and master degree grades are desired. A high level of written and spoken English is also expected.
You may obtain further information from Professor Zheng-Hua Tan, phone: +45 9940 8686, email: firstname.lastname@example.org or Professor Jesper Jensen, phone: +45 9940 8630, email: email@example.com , Department of Electronic Systems, concerning the scientific aspects of the stipend.
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