- Access – Investigation and development of new access techniques (i.e., brain computer interface and multimodal techniques) to achieve more efficient and effective access for individuals with CCN who have severe motor impairments;
- Language support technologies (LanguageTech) – Investigation and invention of AAC technologies to support language use and communication for individuals with CCN who have significant language, cognitive, and /or motor limitations (i.e., technologies that support the transition to literacy for preliterate individuals with CCN, technologies that provide smart prediction to enhance the accuracy, efficiency and independence of communication, and technologies that incorporate video-based visual scene displays (VSDs) to provide dynamic visual supports for communication for those with significant language /cognitive limitations); and
- Human computer interfaces (HCI) – Investigation of techniques to decrease the cognitive processing demands of AAC human computer interfaces and development of tools to improve the person-technology match to enhance communication performance of individuals with CCN.
Access.D1: Developing multimodal technologies to improve access
Project Leaders: Jakobs (InvoTek), Hershberger (Saltillo), Fager, Light, Beukelman, Erdogmus
Consumer Team: Baker, Durfee, Wilson, Cuttlers, Arnold
The goals of this project are to: (1) Develop a new 3-D multimodal access system that provides universal access to all operating systems via a Bluetooth keyboard and mouse interface, and (2) Create a software development kit that enables third-party developers to integrate 3-D multimodal access into their AT devices
LangTech.D2: Developing AAC technology to support interactive video visual scene displays
Project Leaders: Jakobs (InvoTek), Light, Drager, McNaughton
Consumer Team: Rogers, Murray
The goals of this project are: (1) To develop an AAC app for mobile technologies that supports the “just in time” capture and use of video to support interactive communication; and (2) To investigate the effects of this app on communication in real world contexts.
LangTech.D3: Developing a Smart Predictor app for AAC conversation
Team Leaders: Jakobs (InvoTek), Fried-Oken,
Consumer Team: Staehely, Kolden
We will develop a unique prediction system that exploits the shared knowledge of a familiar partner during the creation of written AAC messages. We integrate dynamic, contextual word/phrase prediction from non-disabled partners with a language model in the AAC device to increase speed and informativeness of face-to-face conversations.
HCI.D4: A cognitive demands checklist for AAC technologies and apps
Team Leader: Fried-Oken, Mooney & Bedrick
Consumer Team: Kolden, Staehely
We propose to develop, evaluate and distribute the Cognitive Demands Checklist (CDC), a valid and reliable tool to help developers with the design of AAC technologies and to assist clinicians with the person-technology match.