Abstract
This study compares the translation outputs of an English into Arabic text using the three machine translators of Google Translate, Microsoft Bing, and Ginger. To carry this evaluation of the machine translation (MT) outputs, an English text and its Arabic counterpart were selected from the UN records. The English source text was segmented into 84 semantic chunks. Depending on the Arabic counterpart model text, each chunk was rated as “correct or incorrect” at the two levels of the translation attributes: fidelity and intelligibility. To perform the quantitative description of the evaluation process, the numbers of fidelity and intelligibility errors and their percentages were calculated. Results of this evaluation process revealed that none of the three translated versions of the source text was perfectly translated. Although the translation of Microsoft Bing was rated the best, Google’s translation was found the least accurate due to the high percentage of fidelity and intelligibility errors detected in its translation output. However, the quality of Ginger’s translation was found slightly less accurate than that of Microsoft Bing, but remarkably better than Google’s translation. The findings of this study imply that these MT applications can be implemented to perform English into Arabic translation to get the broad gist of a source text, but a deep and thorough post-editing process looks essential for a full and accurate understanding of an English into Arabic MT output. The study recommends that more studies are encouraged to continue to assess the quality of MT that will further highlight its weaknesses and the strategies that should be adopted to overcome them.
Highlights
Machine translation (MT) which is a subgroup of computational linguistics is defined as “the process that utilizes computer software to translate text from one natural language to another” (Alawneh & Sembok, 2011: p. 343)
Translation quality for each of the output texts would be calculated through the total numbers of fidelity and intelligibility errors and the percentage of total translation errors related to each machine translation (MT) application, and this would eventually lead to identifying the application which would perform a higher quality of the English into Arabic translation
This study aimed to investigate the quality of free MT systems in translating English into Arabic texts
Summary
Machine translation (MT) which is a subgroup of computational linguistics is defined as “the process that utilizes computer software to translate text from one natural language to another” (Alawneh & Sembok, 2011: p. 343). Zong (2018) explains that the process of machine translation relies on the analysis of words, grammar, meaning, and style. This MT process starts by dividing the sentence into words, followed by identifying the meaning of each word through the online dictionary, by analyzing the sentence or clause according to the followed grammar rules in order to convert it into a conceptual construct, and a target language model is used to generate the sentence or text in the TL. If coupled with bidirectional translation software, the automatic translation system can translate multiple languages.” (p. 4)
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