Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
A technique for computer detection and correction of spelling errors
Communications of the ACM
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using the web for language independent spellchecking and autocorrection
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
A large scale ranker-based system for search query spelling correction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Why press backspace?: understanding user input behaviors in Chinese Pinyin input method
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
A unified approach to transliteration-based text input with online spelling correction
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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This paper presents a comparative study of spelling errors that are corrected as you type, vs. those that remain uncorrected. First, we generate naturally occurring online error correction data by logging users' keystrokes, and by automatically deriving pre- and post-correction strings from them. We then perform an analysis of this data against the errors that remain in the final text as well as across languages. Our analysis shows a clear distinction between the types of errors that are generated and those that remain uncorrected, as well as across languages.