Predicting sentences using N-gram language models

Authors:
Steffen Bickel;Peter Haider;Tobias Scheffer
Affiliations:
Humboldt-Universität zu Berlin, Berlin, Germany;Humboldt-Universität zu Berlin, Berlin, Germany;Humboldt-Universität zu Berlin, Berlin, Germany
Venue:
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Year:
2005

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Abstract

We explore the benefit that users in several application areas can experience from a "tab-complete" editing assistance function. We develop an evaluation metric and adapt N-gram language models to the problem of predicting the subsequent words, given an initial text fragment. Using an instance-based method as baseline, we empirically study the predictability of call-center emails, personal emails, weather reports, and cooking recipes.