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Effectiveness of Context-Aware Character Input Method for Mobile Phone Based on Artificial Neural Network
Author(s) -
Masafumi Matsuhara,
Satoshi Suzuki
Publication year - 2012
Publication title -
applied computational intelligence and soft computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 10
eISSN - 1687-9732
pISSN - 1687-9724
DOI - 10.1155/2012/896948
Subject(s) - computer science , kana , kanji , sentence , string (physics) , mobile phone , input method , character (mathematics) , artificial neural network , artificial intelligence , context (archaeology) , phone , natural language processing , speech recognition , chinese characters , telecommunications , paleontology , linguistics , philosophy , physics , geometry , mathematics , quantum mechanics , biology
Opportunities and needs are increasing to input Japanese sentences on mobile phones since performance of mobile phones is improving. Applications like E-mail, Web search, and so on are widely used on mobile phones now. We need to input Japanese sentences using only 12 keys on mobile phones. We have proposed a method to input Japanese sentences on mobile phones quickly and easily. We call this method number-Kanji translation method. The number string inputted by a user is translated into Kanji-Kana mixed sentence in our proposed method. Number string to Kana string is a one-to-many mapping. Therefore, it is difficult to translate a number string into the correct sentence intended by the user. The proposed context-aware mapping method is able to disambiguate a number string by artificial neural network (ANN). The system is able to translate number segments into the intended words because the system becomes aware of the correspondence of number segments with Japanese words through learning by ANN. The system does not need a dictionary. We also show the effectiveness of our proposed method for practical use by the result of the evaluation experiment in Twitter data

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