Using the web for language independent spellchecking and autocorrection

Using the web for language independent spellchecking and autocorrection (2009)

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by Ben Hutchinson , Grace Y Chung , Gerard Ellis

Venue:	In EMNLP
Citations:	6 - 0 self

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Datum	Value	Source
TITLE	Using the web for language independent spellchecking and autocorrection	INFERENCE
AUTHOR NAME	Ben Hutchinson	SVM HeaderParse 0.2
AUTHOR AFFIL	Google Inc.	SVM HeaderParse 0.2
AUTHOR ADDR	Level 5, 48 Pirrama Rd, Pyrmont NSW 2009, Australia	SVM HeaderParse 0.2
AUTHOR NAME	Grace Y Chung	SVM HeaderParse 0.2
AUTHOR AFFIL	Google Inc.	SVM HeaderParse 0.2
AUTHOR ADDR	Level 5, 48 Pirrama Rd, Pyrmont NSW 2009, Australia	SVM HeaderParse 0.2
AUTHOR NAME	Gerard Ellis	SVM HeaderParse 0.2
AUTHOR AFFIL	Google Inc.	SVM HeaderParse 0.2
AUTHOR ADDR	Level 5, 48 Pirrama Rd, Pyrmont NSW 2009, Australia	SVM HeaderParse 0.2
ABSTRACT	We have designed, implemented and evaluated an end-to-end system spellchecking and autocorrection system that does not require any manually annotated training data. The World Wide Web is used as a large noisy corpus from which we infer knowledge about misspellings and word usage. This is used to build an error model and an n-gram language model. A small secondary set of news texts with artificially inserted misspellings are used to tune confidence classifiers. Because no manual annotation is required, our system can easily be instantiated for new languages. When evaluated on human typed data with real misspellings in English and German, our web-based systems outperform baselines which use candidate corrections based on hand-curated dictionaries. Our system achieves 3.8 % total error rate in English. We show similar improvements in preliminary results on artificial data for Russian and Arabic. 1	SVM HeaderParse 0.2
YEAR	2009	INFERENCE
VENUE	In EMNLP	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	890--899	INFERENCE
CITATIONS	18 found	ParsCit 1.0