TITLE:		WORD PREDICTION FOR DISABLED USERS: APPLYING NATURAL
		LANGUAGE PROCESSING TO ENHANCE COMMUNICATION
AUTHOR:		Julie A. Van Dyke
COMMENTS:	(c) 1991 Julie A. Van Dyke

ABSTRACT:
Disorders such as Cerebral Palsy and Lou Gehrig's disease produce
severe physical disabilities that make normal communication
impossible. This project addresses this problem by developing a
syntactic prediction system. Other communication aids have previously
been developed using abbreviation and prediction to enhance
communication, but these have had limited success. Abbreviation
systems allow the user to type pre-determined, shortened word-forms
which the computer is responsible for expanding.  Prediction systems
attempt to predict the user's next keystrokes based on statistical
data.

I have combined natural language processing techniques and popular
syntax theories to devise a prediction system that, unlike these
previous systems, models the syntax rules that specify how words can
be combined. This allows the syntactic predictor to make rule-based,
linguistic determinations about what words can follow those already
processed. It can be used with flexible abbreviation systems to
eliminate possible expansions for personalized abbreviations. The
syntactic predictor could also be used with other devices to reduce
the effort required of the user by predicting what word forms he or
she is likely to type next. In modelling linguistic knowledge, this
system provides a more natural solution to the communication problem
than many systems currently in use.