Abstract: Machine translation is an active research domain in fields of artificial intelligence. The relevant literature presents a number of machine translation approaches for the translation of different languages. Urdu is the national language of Pakistan while Arabic is a major language in almost 20 different countries of the world comprising almost 450 million people. To the best of our knowledge, there is no published research work presenting any method on machine translation from Urdu to Arabic, however, some online machine translation systems like Google , Bing and Babylon provide Urdu to Arabic machine translation facility. In this paper, we compare the performance of online machine translation systems. The input in Urdu language is translated by the systems and the output in Arabic is compared with the ground truth data of Arabic reference sentences. The comparative analysis evaluates the systems by three performance evaluation measures: BLEU (BiLingual Evaluation Understudy), METEOR (Metric for Evaluation of Translation with Explicit ORdering) and NIST (National Institute of Standard and Technology) with the help of a standard corpus. The results show that Google translator is far better than Bing and Babylon translators. It outperforms, on the average, Babylon by 28.55% and Bing by 15.74%.

Maheen Akhter Ayesha, Sahar Noor, Muhammad Ramzan and Hikmat Ullah Khan, “Evaluating Urdu to Arabic Machine Translation Tools” International Journal of Advanced Computer Science and Applications(IJACSA), 8(10), 2017. http://dx.doi.org/10.14569/IJACSA.2017.081012

@article{Ayesha2017,
title = {Evaluating Urdu to Arabic Machine Translation Tools},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.081012},
url = {http://dx.doi.org/10.14569/IJACSA.2017.081012},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {10},
author = {Maheen Akhter Ayesha and Sahar Noor and Muhammad Ramzan and Hikmat Ullah Khan}
}