2009 AnUnsupervisedModelforTextMessa

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Subject Headings: Lexical Normalization, SMS, Texting Language.

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Abstract

Cell phone text messaging users express themselves briefly and colloquially using a variety of creative forms. We analyze a sample of creative, non-standard text message word forms to determine frequent word formation processes in texting language. Drawing on these observations, we construct an unsupervised noisy-channel model for text message normalization. On a test set of 303 text message forms that differ from their standard form, our model achieves 59% accuracy, which is on par with the best supervised results reported on this dataset.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2009 AnUnsupervisedModelforTextMessaPaul Cook
Suzanne Stevenson
An Unsupervised Model for Text Message Normalization