Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
Pronunciation modeling for improved spelling correction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
A statistical text-to-phone function using ngrams and rules
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
On using context for automatic correction of non-word misspellings in student essays
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
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We propose a method for modeling pronunciation variation in the context of spell checking for non-native writers of English. Spell checkers, typically developed for native speakers, fail to address many of the types of spelling errors peculiar to non-native speakers, especially those errors influenced by differences in phonology. Our model of pronunciation variation is used to extend a pronouncing dictionary for use in the spelling correction algorithm developed by Toutanova and Moore (2002), which includes models for both orthography and pronunciation. The pronunciation variation modeling is shown to improve performance for misspellings produced by Japanese writers of English.