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

机译:基于人工神经网络的手机上下文感知字符输入方法的有效性

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摘要

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.
机译:由于手机性能的提高,在手机上输入日语句子的机会和需求正在增加。如今,电子邮件,Web搜索等应用程序已在移动电话上广泛使用。我们只需要在手机上使用12个键输入日语句子。我们提出了一种在手机上快速轻松地输入日语句子的方法。我们称此方法编号为汉字翻译方法。在我们提出的方法中,将用户输入的数字字符串翻译为汉字-假名混合句子。数字字符串到假名字符串是一对多映射。因此,很难将数字字符串转换为用户想要的正确句子。所提出的上下文感知映射方法能够通过人工神经网络(ANN)消除数字字符串的歧义。该系统能够将数字段转换为预期的单词,因为该系统通过ANN学习得知数字段与日语单词的对应关系。系统不需要字典。通过Twitter数据中的评估实验结果,我们还展示了我们提出的方法在实际使用中的有效性。

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  • 来源
    《Applied computational intelligence and soft computing》 |2012年第2012期|896948.1-896948.6|共6页
  • 作者单位

    Department of Software and Information Science, Iwate Prefectural University, 152-52, Takizawa, Iwate 020-0193, Japan;

    Supernet Department, System Consultant Co., Ltd., 2-14-6, Kinshi, Sumida, Tokyo 130-0013, Japan;

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