Machine Learning Applied to Multi-Modal Interaction, Adaptive Interfaces and Ubiquitous Assistive Technologies

author: Jaisiel Madrid-Sanchez, Carlos III University of Madrid
published: Jan. 19, 2010,   recorded: December 2009,   views: 2826


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The presentation will describe the challenge of eInclusion in the technological design process, which impedes the complete integration of people with disabilities and elderly in Information Society. To face this challenge, the INREDIS project aims to face individual needs of users instead of addressing the needs of the average user, by proposing basic technologies that enables the creation of personalized channels for communication and interaction with the technological environment. For this purpose, Machine Learning can help constructing effective methods to reflect user needs, preferences and expectations (and their evolution over time) on user interfaces, consequently improving satisfaction and performance. In particular, academia and industry within the INREDIS consortium explore together the potential of Machine Learning on multimodal services and ubiquitous assistive technologies, as well as adaptive user interfaces according to user and technological capabilities.

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