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%.
Highlights
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
We repot the results which are generated by our evaluation metrics (BLEU, METEOR and National Institute of Standard and Technology (NIST)) for the corpus which we mentioned above
By calculating the average of all three sentence types, we see that Google gives 0.1164, Babylon 0.0473 and Bing 0.0783 BiLingual Evaluation Understudy (BLEU) score
Summary
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. Among 7,105 languages spoken in different areas of the world, Urdu is ranked at 19th number.. The main information sources such as newspapers and electronic media use Urdu language [1]. Arabic is the main language in 20 different countries like Egypt, Iraq, Saudi Arabia, Somalia, Sudan, Syria and the United Arab Emirates [2]. Different MT techniques such as Rule-based [3], [4], Direct [6], Transfer [5], Statistical [6], Interlingua [7], Example based [8], Knowledge-base [9] and Hybrid Machine Translation [10], [11] (MT) are used to translate from one language to the other. We use the terms “translator”, “MT system” and “MT tool” interchangeably
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