A methodology for machine translation of simple sentences from Kannada to English language

M. Kodabagi, S. Angadi
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引用次数: 1

Abstract

In this paper, a new approach for machine translation of simple sentences from Kannada to English language is presented. Initially, the method performs lexical analysis to process input transliterated Kannada sentence to recognize and classify tokens using newly constructed source language lexicon KannadaWordNet. Then, newly designed recursive descent parser for the domain validates the transliterated Kannada sentence with the syntactic constructs/grammar rules. Further, the phrase mapper and output generation mechanisms are employed to obtain translated English sentence. The proposed methodology is evaluated on a data set containing transliterated Kannada sentences of text written in low resolution images of display boards of Karnataka government offices in India. The method achieves an average translation accuracy of 97.56%. The proposed method is robust and efficient in dealing with various issues such as construction of source lexicon, syntactic/semantic representation of language constructs, design of efficient parser, resolving differences between syntactic/semantic constructs of source and target language, construction of bilingual dictionary. The method also resolves word sense ambiguity, translation ambiguity, and provides accurate translation without errors.
从卡纳达语到英语简单句的机器翻译方法
本文提出了一种从卡纳达语到英语的简单句机器翻译的新方法。首先,该方法使用新构建的源语言词汇库KannadaWordNet对输入的音译的卡纳达语句子进行词法分析,从而识别和分类标记。然后,针对该领域设计递归下降解析器,使用语法结构/语法规则对音译后的卡纳达语句子进行验证。在此基础上,利用短语映射器和输出生成机制获取翻译后的英语句子。在印度卡纳塔克邦政府办公室展示板的低分辨率图像中,对包含音译的卡纳达语文本句子的数据集进行了评估。该方法的平均翻译准确率为97.56%。该方法在源语词典的构建、语言结构的句法/语义表示、高效解析器的设计、源语和目标语句法/语义结构差异的消解、双语词典的构建等方面具有鲁棒性和高效性。该方法还解决了词义歧义、翻译歧义等问题,实现了准确无误的翻译。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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