Towards an intelligent multilingual keyboard system

Authors:
Tanapong Potipiti;Virach Sornlertlamvanich;Kanokwut Thanadkran
Affiliations:
Ministry of Science and Technology Environment, Bangkok, Thailand;Ministry of Science and Technology Environment, Bangkok, Thailand;Ministry of Science and Technology Environment, Bangkok, Thailand
Venue:
HLT '01 Proceedings of the first international conference on Human language technology research
Year:
2001

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Abstract

This paper proposes a practical approach employing n-gram models and error-correction rules for Thai key prediction and Thai-English language identification. The paper also proposes rule-reduction algorithm applying mutual information to reduce the error-correction rules. Our algorithm reported more than 99% accuracy in both language identification and key prediction.