Abstract
Online text machine translation systems are widely used throughout the world freely. Most of these systems use statistical machine translation (SMT) that is based on a corpus full with translation examples to learn from them how to translate correctly. Online text machine translation systems differ widely in their effectiveness, and therefore we have to fairly evaluate their effectiveness. Generally the manual (human) evaluation of machine translation (MT) systems is better than the automatic evaluation, but it is not feasible to be used. The distance or similarity of MT candidate output to a set of reference translations are used by many MT evaluation approaches. This study presents a comparison of effectiveness of two free online machine translation systems (Google Translate and Babylon machine translation system) to translate Arabic to English. There are many automatic methods used to evaluate different machine translators, one of these methods; Bilingual Evaluation Understudy (BLEU) method. BLEU is used to evaluate translation quality of two free online machine translation systems under consideration. A corpus consists of more than 1000 Arabic sentences with two reference English translations for each Arabic sentence is used in this study. This corpus of Arabic sentences and their English translations consists of 4169 Arabic words, where the number of unique Arabic words is 2539. This corpus is released online to be used by researchers. These Arabic sentences are distributed among four basic sentence functions (declarative, interrogative, exclamatory, and imperative). The experimental results show that Google machine translation system is better than Babylon machine translation system in terms of precision of translation from Arabic to English.
Highlights
Machine translation means the use of the computers to translate from one natural language into another
In our evaluation and testing of the two Machine Translation (MT) systems, we found that the translation precision is equal for both MT systems (Google and Babylon) for some sentences, but translation precision of Google Translate is generally better than translation precision of Babylon MT system (0.45 for Google and 0.40 for Babylon)
We have evaluated the effectiveness of two automatic machine translators (Google Translate System and Babylon machine translation system) that could be used for Arabic-to-English translation and vice versa
Summary
Machine translation means the use of the computers to translate from one natural language into another. The translation accuracy of online machine translation (MT) systems is lower than translation accuracy of professional translators, these systems are widely used by different people around the world due to their speed and free cost. Online machine translators rely on different approaches to translate from one natural language into another, these approaches are Rule-based, Direct, Interlingua, Transfer, Statistical, Example-based, Knowledge-based, and Hybrid Machine Translation (MT). The automatic evaluation of machine translation systems is based on a comparison of MT outputs and the corresponding professional human translations (Reference translations). The first methods to automatic Machine Translation evaluation are based on lexical similarity. These are known as Lexical measures (n-gram-based measures) and are based on lexical matching between MT systems outputs and corresponding reference translations [1]
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