We are working on communication interfaces for people with speech and language disorders, incorporating technologies like physiological sensing and personalized machine learning. As part of our research, we conducted a survey to better understand how existing devices are used, and what architectures and features might be useful in new devices.
De-identified quantitative data can be downloaded and viewed in GUI via the attached file MATLAB_Publish.zip. Please cite use of this data as:
Narain, J., and Maes, P. "Understanding AAC Usage and Needs through a Web Survey with Device Users and Families". Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society. 2020.
Sources for logo: Spell deaf talk speech, Information Computer Technology Digital Binary, Alternative Handicapped Accessible sign
