A new statistical approach to Chinese Pinyin input
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Chinese lexical analysis using hierarchical hidden Markov model
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
A segment-based hidden markov model for real-setting pinyin-to-chinese conversion
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A novel statistical chinese language model and its application in pinyin-to-character conversion
Proceedings of the 17th ACM conference on Information and knowledge management
Chinese Pinyin-Text Conversion on Segmented Text
TSD '09 Proceedings of the 12th International Conference on Text, Speech and Dialogue
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Social Network Service (SNS) and personal blogs have become the most popular platform for online communication and sharing information. However because most modern computer keyboards are Latin-based, Asian language speakers (such as Chinese) has to rely on a input system which accepts Romanisation of the characters and convert them into characters or words in that language. In Chinese this form of Romanisation (usually called Pinyin) is highly ambiguous, word misuses often occur because the user choose a wrong candidate or deliverately substitute the word with another character string that has the identical Romanisation to convey certain semantics, or to achieve a sarcasm effect. In this paper we aim to develop a system that can automatically identify such word misuse, and suggest the correct word to be used.