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ARABIC-MALAY MACHINE TRANSLATION USING RULE-BASED APPROACH | Science Publications

机译:基于规则的方法进行阿拉伯-马来语机器翻译科学出版物

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> Arabic machine translation has been taking place in machine translation projects in recent years. This study concentrates on the translation of Arabic text to its equivalent in Malay language. The problem of this research is the syntactic and morphological differences between Arabic and Malay adjective sentences. The main aim of this study is to design and develop Arabic-Malay machine translation model. First, we analyze the adjective role in the Arabic and Malay languages. Based on this analysis, we identify the transfer bilingual rules form source language to target language so that the translation of source language to target language can be performed by computers successfully. Then, we build and implement a machine translation prototype called AMTS to translate from Arabic to Malay based on rule based approach. The system is evaluated on set of simple Arabic sentences. The techniques used to evaluate the correctness of the system translation are the BLEU metric algorithm and the human judgment. The results of the BLEU algorithm show that the AMTS system performs better than Google in the translation of Arabic sentences into Malay. In addition, the average accuracy given by human judges is 92.3% for our system and 75.3% for Google.
机译: >近年来,阿拉伯机器翻译已在机器翻译项目中进行。这项研究集中于将阿拉伯文本翻译成与马来语等效的文本。这项研究的问题是阿拉伯和马来形容词句子的句法和词法差异。这项研究的主要目的是设计和开发阿拉伯语-马来语机器翻译模型。首先,我们分析阿拉伯语和马来语中的形容词作用。基于此分析,我们确定了从源语言到目标语言的转移双语规则,以便计算机可以成功地执行源语言到目标语言的翻译。然后,我们建立并实现了一个称为AMTS的机器翻译原型,它基于基于规则的方法将阿拉伯语翻译为马来语。该系统根据一组简单的阿拉伯文句子进行评估。用于评估系统翻译正确性的技术是BLEU度量算法和人为判断。 BLEU算法的结果表明,在将阿拉伯文句子翻译成马来语方面,AMTS系统的性能要优于Google。此外,人类裁判给出的平均准确度对于我们的系统是92.3%,对于Google是75.3%。

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