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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移动电话情报输入方法的有效性

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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:由于手机的性能正在改善,因此在移动电话上输入日语句子的机会和需求正在增加。现在是电子邮件,网络搜索等的应用程序现在广泛用于移动电话。我们需要在手机上只使用12个键输入日语句子。我们提出了一种快速轻松地在手机上输入日语句子的方法。我们调用此方法编号-Kanji翻译方法。用户输入的数字字符串以我们提出的方法翻译成Kanji-Kana混合句子。 kana字符串的数字字符串是一对多映射。因此,难以将数字字符串转换为用户的正确句子。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。该系统能够将数字段转换为预期的单词,因为系统通过ANN学习通过学习时意识到数字段的对应关系。系统不需要字典。我们还展示了我们提出的方法来实际使用的效果,通过在Twitter数据中的评估实验结果。

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