Adaptive predictive text generation and the reactive keyboard

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Abstract
The 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 modelling mechanism. The basic idea is to order context-conditioned candidate strings, which are predicted by the model, according to frequency and display them for selection.