IJLLL 2018 Vol.4(3): 231-235 ISSN: 2382-6282
DOI: 10.18178/IJLLL.2018.4.3.178

Assessment of Google and Microsoft Bing Translation of Journalistic Texts

Zakaryia Mustafa Almahasees
Abstract—Machine Translation (MT) systems are commonly utilized by end users since MT is available freely or at a low cost. The increasing demand for MT services nowadays means that ensuring the acceptability of the output to the potential users of such systems is a necessary task. The paper evaluates the capacity of two prominent systems, Google Translate and Microsoft Bing Translator, in producing acceptable English translations of journalistic texts written in Arabic. To do so, the study has adopted Linguistic Error Analysis of Reference [1] and of Error Classification described in Reference [2]. The results of the study show that both systems obtain outstanding results with > 90 percentage accuracy in the area of orthography and grammar. In addition, both systems obtain good results in the areas of lexical and grammatical collocations of 79.8% for Google and 74.5% for Bing. The two systems achieved good results in these categories because they have recently adopted Neural Machine Translation, which imitates the human brain to perform translation and learns from previously translated texts by humans. For future research, the study recommends conducting more assessment on translation in a variety of fields of knowledge using Linguistic Error Analysis. Machine Translation is still far from reaching fully automatic translation of a quality obtainable by human translators.

Index Terms—Google translate, assessment, microsoft bing, Machine Translation Evaluation (MTE), machine translation errors.
 
Zakaryia Mustafa Almahasees is with the University of Western Australia, School of Humanities, Research Grants (Research Travel Grant), Zakaryia Almahasees is with University of Western Australia, Australia (e-mail: zakaryia.almahasees@research.uwa.edu.au).

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Cite:Zakaryia Mustafa Almahasees, "Assessment of Google and Microsoft Bing Translation of Journalistic Texts," International Journal of Languages, Literature and Linguistics vol. 4, no. 3, pp. 231-235, 2018.

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