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Applied Computational Intelligence and Soft Computing
Volume 2012, Article ID 896948, 6 pages
Research Article

Effectiveness of Context-Aware Character Input Method for Mobile Phone Based on Artificial Neural Network

1Department of Software and Information Science, Iwate Prefectural University, 152-52, Takizawa, Iwate 020-0193, Japan
2Supernet Department, System Consultant Co., Ltd., 2-14-6, Kinshi, Sumida, Tokyo 130-0013, Japan

Received 10 February 2012; Revised 19 April 2012; Accepted 26 April 2012

Academic Editor: Cheng-Hsiung Hsieh

Copyright © 2012 Masafumi Matsuhara and Satoshi Suzuki. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.