The acceleration in telecommunication needs leads to many groups of research, especially in communication facilitating and Machine Translation fields. While people contact with others having different languages and cultures, they need to have instant translations. However, the available instant translators are still providing somewhat bad Arabic-English Translations, for instance when translating books or articles, the meaning is not totally accurate. Therefore, using the semantic web techniques to deal with the homographs and homonyms semantically, the aim of this research is to extend a model for the ontology-based Arabic-English Machine Translation, named NAN, which simulate the human way in translation. The experimental results show that NAN translation is approximately more similar to the Human Translation than the other instant translators. The resulted translation will help getting the translated texts in the target language somewhat correctly and semantically more similar to human translations for the Non-Arabic Natives and the Non-English natives.
翻译:电信需求的加速导致许多研究团体,特别是在通讯便利和机器翻译领域。人们与具有不同语言和文化的其他人接触时,需要即时翻译。然而,现有的即时翻译员仍然提供一些差劲的阿拉伯文-英文翻译,例如翻译书籍或文章时,其意义并不完全准确。因此,使用语义网络技术处理同义词和同义词的语义,这项研究的目的是推广一个以本体为基础的阿拉伯文-英文机器翻译模型,名为NAN,模拟人文翻译方式。实验结果显示,NAN翻译比其他即时翻译者更类似于人文翻译,其结果将有助于非阿拉伯原住民和非英语本地人的翻译,以目标语言翻译的文字略为正确,语义也更类似人文翻译。