Intelligent Word Prediction uses knowledge of syntax and word
frequencies to predict the next word in a sentence as the sentence is
being entered, and updates this prediction as the word is typed. The
intended application of this project is to accelerate and facilitate
the entry of words into an augmentative communication device by
offering a shortcut to typing entire words. A prototype version has
been written in LISP, using an ATN probabilistic parser and a lexicon
containing word frequencies and subcategorizations.
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Contributors
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The goal of this project is to develop a word prediction system to
assist individuals with disabilities who use alternative and
augmentative communication (AAC). By modelling the linguistic
constraints that apply to a sentence, the system predicts the next
word to be produced in the sentence, and narrows the prediction search
as each subsequent letter of the word is entered. Applying this
technique to AAC would facilitate and accelerate augmented
communication by offering a shortcut to typing all the words in their
entirety.
A long term goal is to unify this project with our Compansion and
Language Representation Database projects, in order to
incorporate a more sophisticated body of linguistic information into
augmentative communication systems. Consistent with this goal, an
important implementation goal is to develop code that is
object-oriented and modular.
The first word of the sentence is predicted on the basis of the
frequency of words in the sentence-initial position. Each word is
incorporated into an augmented transition network (ATN), with a branch
for every acceptable syntactic interpretation of the sentence segment
so far.
The grammar contains probabilities for each ATN structure, and the
lexicon contains the frequencies with which words occur in each of
their possible subcategorizations. Combining these statistics results
in a list of possible next words, the 5 most probable of which are
offered to the user. The user may reject the predicted word list and
begin entering the word by hand. As each letter is entered, words that
are not consistent with the word segment entered so far are filtered
out, and the prediction list is updated.
It is assumed that the words in the sentence are entered in
correct grammatical order. The accuracy of the system's predictions
will depend on the accuracy of the syntactic rule probabilities and
word frequencies.