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Computational Interaction$
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Antti Oulasvirta, Per Ola Kristensson, Xiaojun Bi, and Andrew Howes

Print publication date: 2018

Print ISBN-13: 9780198799603

Published to Oxford Scholarship Online: March 2018

DOI: 10.1093/oso/9780198799603.001.0001

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Statistical Language Processing for Text Entry

Statistical Language Processing for Text Entry

Chapter:
(p.43) 2 Statistical Language Processing for Text Entry
Source:
Computational Interaction
Author(s):

Per Ola Kristensson

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198799603.003.0003

In this chapter we explain how methods from statistical language processing serve as a foundation for the design of probabilistic text entry methods and error correction methods. We review concepts from information theory and language modelling and explain how to design a statistical decoder for text entry—a generative probabilistic model based on the token-passing paradigm. We then present five example applications of statistical language processing for text entry: correcting typing mistakes, enabling fast typing on a smartwatch, improving prediction in augmentative and alternative communication, enabling dwell-free eye-typing and intelligently supporting error correction of probabilistic text entry. We then discuss the limitations of the models presented in this chapter and highlight the importance of establishing solution principles based on engineering science and empirical research in order to guide the design of probabilistic text entry.

Keywords:   Text entry, statistical decoder, language model, keyboard

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