Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
Text input for mobile devices: comparing model prediction to actual performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
Word-sense disambiguation using statistical methods
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Word-based predictive text entry using adaptive language models
Natural Language Engineering
| Hi-index | 0.00 |
Predictive text entry systems on computers like kana-to-kanji conversion provide a mechanism that enables users to select among possible words for a given input. Mistakes in selection are relatively common, and they introduce real-word errors. A proofreading system is thus needed to detect and correct real-word errors on a computer without imposing troublesome operations on users. To this end, a practical proofreading system for Japanese text is proposed. The system automatically detects possible real-word homonym errors, and for each detected word, suggests substitution candidates of the same pronunciation. The user can either choose the most appropriate one or leave the original untouched. The system uses an algorithm based on the Naïve Bayesian method. Although the proofreading system was implemented for homonym errors in Japanese text, its design concept and algorithm are also applicable to other languages. The client program of the proofreading system is implemented on the Emacs text editor and works in real time.