一种基于人工神经网络的高效上下文感知手机字符输入算法

Masafumi Matsuhara, Satoshi Suzuki
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引用次数: 5

摘要

随着手机性能的提高,在手机上输入日语句子的机会和需求也在增加。像电子邮件、网络搜索等应用程序现在在手机上被广泛使用。我们需要在手机上用12个键输入日语句子。我们提出了一种在手机上快速方便地输入日语句子的方法。我们称这种方法为数字-汉字翻译法。用户输入的数字-字符串转换成字符串到名称-字符串是一对多的映射。因此,很难将数字字符串翻译成用户想要的正确句子。本文提出的上下文感知映射方法能够利用人工神经网络(ANN)消除数字字符串的歧义。通过人工神经网络的学习,系统意识到数字段与日语单词的对应关系,因此系统能够将数字段翻译成预期的单词。系统不需要字典。通过评价实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An efficient context-aware character input algorithm for mobile phone based on artificial neural network
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 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 by the result of the evaluation experiment.
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