A Pilot Study of Biber's Model for Language Variation Detection: A Language Engineering Approach | ||||
| The Egyptian Journal of Language Engineering | ||||
| Article 3, Volume 7, Issue 2, September 2020, Page 32-40 PDF (1.34 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ejle.2020.37903.1009 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Maram Elsaadany   1; Sameh Alansary2
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| 1English ,Faculty of Arts, Alexandria University | ||||
| 2Faculty of Arts, Alexandria University | ||||
| Abstract | ||||
| Abstract — this paper is primarily a translation analysis of Tramp’s speech and a letter sent to President Trump regarding family separation on “The Leadership Conference on Civil and Human Rights” to locate the differences in translation found between written and speech texts. Google translate is the engine used to translate these two texts into Arabic. The data selected for this analysis is 1000 words in each script. Biber’s model (1988) used 67 features to prove that writing is more complicated than speech. The study enforces Biber’s claim that writing is more complicated than speech. The findings assure Biber’s claim as there were lots of problems in the translation of the speech text into Arabic in comparison to the translated written texts. Our findings strongly support the view that academic writing and conversation have dramatically different linguistic characteristics .The Results clarify the fact that google translate has to be adapted and equipped with a new grammar for speech that is different than the one used for writing to achieve the best outcome for both translations in the same language. This paper is a pioneer in its application as there is no research paper adapted such approach in the field of translation. | ||||
| Keywords | ||||
| translation; computational; linguistic variations; speech; writing | ||||
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