ADAPTIVE PREDICTIVE TEXT GENERATION AND THE REACTIVE KEYBOARD
Date
1989-05-01
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Abstract
This paper explores the application of predictive text generation to
the human-computer interface. Predictive techniques exploit the statistical
redundancy of language to accelerate and amplify user inputs. Acceleration
is achieved by making more likely language elements faster to select, while
amplification is accomplished by selection of concatenated elements. The
language models used are created adaptively, decoupling the prediction
mechanism from the application domain and user's vocabulary, and conforming
automatically to whatever kind of text is entered.
A device called the Reactive Keyboard is described along with two
user interface implementations, one for keyboard entry and the other for a
mouse/window environment. A clear separation is made between the system's
user interface and the underlying model it employs, and the two versions
share the same prediction technique and adaptive modeling mechanism. The
basic idea is to order context-conditioned candidate strings, which are
predicted by the model, according to popularity and display them for
selection.
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Computer Science