IEEE Transactions on Pattern Analysis and Machine Intelligence
A technique for computer detection and correction of spelling errors
Communications of the ACM
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Toward a unified approach to statistical language modeling for Chinese
ACM Transactions on Asian Language Information Processing (TALIP)
A spelling correction program based on a noisy channel model
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
Pronunciation modeling for improved spelling correction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
A new statistical approach to Chinese Pinyin input
ACL '00 Proceedings of the 38th 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
Corpus-based Pinyin name resolution
SIGHAN '02 Proceedings of the first SIGHAN workshop on Chinese language processing - Volume 18
Efficient interactive fuzzy keyword search
Proceedings of the 18th international conference on World wide web
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
Learning phrase-based spelling error models from clickthrough data
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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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Chinese Pinyin input methods are very important for Chinese language processing. In many cases, users may make typing errors. For example, a user wants to type in "shenme" (???, meaning "what" in English) but may type in "shenem" instead. Existing Pinyin input methods fail in converting such a Pinyin sequence with errors to the right Chinese words. To solve this problem, we developed an efficient error-tolerant Pinyin input method called "CHIME" that can handle typing errors. By incorporating state-of-the-art techniques and language-specific features, the method achieves a better performance than state-of-the-art input methods. It can efficiently find relevant words in milliseconds for an input Pinyin sequence.