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ACE-LP: Augmenting Communication using Environmental Data to drive Language Prediction

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Nonspeaking disabled people who use Speech Generating Devices (SGDs) communicate an average of between 8 and 12 words per minute (wpm) compared to typical adult speech of 150-190 wpm. For some, e.g., Prof Stephen Hawking who relies on a single switch access, rates fall to 1-2 wpm.

The ACE-LP project aims to develop a communication system for nonspeaking people which will improve on the speed of communication by automatically populating the system with appropriate conversational items within an adaptive interface that provides control over timing and delivery whilst minimising physical and cognitive load.

To achieve this, we will, for the first time, combine probabilistic language prediction with contextual data from sources such as video, audio and positional sensors, supplemented with user profiles and past experience, to present appropriate conversational information within an interface that adapts to the needs of users.

The ACE-LP project is in its very early stages and with this poster we will introduce our idea to seek discussion with and feedback from a specialist audience to inform our research and design.


Rolf Black    
University of Dundee
United Kingdom

Per Ola Kristensson, Dr P    
University of Cambridge
United Kingdom

Stephen J. McKenna    
University of Dundee

Jianguo Zhang    
University of Dundee

Annalu Waller    
University of Dundee


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