PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Dynamics and probabilistic text entry
John Williamson and Roderick Murray-Smith
In: Proceedings of the Hamilton Summer School on Switching and Learning in Feedback systems (2005) Springer , Berlin, Germany , pp. 333-342.

Abstract

We present a gestural interface for entering text on a mobile device via continuous movements, with control based on feedback from a probabilistic language model. Text is represented by continuous trajectories over a hexagonal tessellation, and entry becomes a manual control task. The language model is used to infer user intentions and provide predictions about future actions, and the local dynamics adapt to reduce effort in entering probable text. This leads to an interface with a stable layout, aiding user learning, but which appropriately supports the user via the probability model. Experimental results demonstrate that the application of this technique reduces variance in gesture trajectories, and is competitive in terms of throughput for mobile devices. This paper provides a practical example of a user interface making uncertainty explicit to the user, and probabilistic feedback from hypothesised goals has general application in many gestural interfaces, and is well-suited to support multimodal interaction.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
User Modelling for Computer Human Interaction
Multimodal Integration
ID Code:1274
Deposited By:Roderick Murray-Smith
Deposited On:28 November 2005