How to cite this paper
Al-Salman, S & Haider, A. (2024). Assessing the accuracy of MT and AI tools in translating humanities or social sciences Arabic research titles into English: Evidence from Google Translate, Gemini, and ChatGPT.International Journal of Data and Network Science, 8(4), 2483-2498.
Refrences
Abdelaal, N. M., & Alazzawie, A. (2020). Machine Translation: The Case of Arabic-English Translation of News Texts. Theory & Practice in Language Studies, 10(4). doi:http://dx.doi.org/10.17507/tpls.1004.09
Akasheh, W. M., Haider, A. S., Al-Saideen, B., & Sahari, Y. (2024). Artificial intelligence-generated Arabic subtitles: in-sights from Veed. io's automatic speech recognition system of Jordanian Arabic. Texto Livre, 17, e46952-e46952. doi:10.1590/1983-3652.2024.46952.
Al-Salman, S., & Haider, A. S. (2021). TheRrepresentation of Covid-19 and China in Reuters’ and Xinhua’s Headlines. Search (Malaysia), 13(1), 93-110. doi:https://fslmjournals.taylors.edu.my/wp-content/uploads/SEARCH/SEARCH-2021-13-1/SEARCH-2021-P8-13-1.pdf
Almahasees, Z. (2018). Assessment of Google and Microsoft Bing translation of journalistic texts. International Journal of Languages, Literature and Linguistics, 4(3), 231-235.
Almahasees, Z. (2021). Analysing English-Arabic Machine Translation: Google Translate, Microsoft Translator and Sakhr. London: Routledge.
Almahasees, Z., & Jaccomard, H. (2020). Facebook Translation Service (FTS) Usage among Jordanians during COVID-19 Lockdown. Advances in Science, Technology and Engineering Systems Journal, 5(6), 514-519. doi:10.25046/aj050661
Alrousan, F., & Haider, A. S. (2022). Dubbing television advertisements across cultures and languages: A case study of English and Arabic. Language Value, 15(2), 54-80. doi:https://doi.org/10.6035/languagev.6922
Aydin, Ö. (2023). Google Bard generated literature review: metaverse. Journal of AI, 7(1), 1-14.
Bin Dahmash, N. (2020). ‘I Can't Live Without Google Translate’: A Close Look at the Use of Google Translate App by Second Language Learners in Saudi Arabia. Arab World English Journal (AWEJ) Volume, 11(3), 226-240
Bouguesmia, M. T. (2020). Using AI in Translation, a Technological Leap, or a Translator’s Nightmare. ALTRALANG Journal, 2(02), 78-102.
Bowman, D., & Kinnan, S. (2018). Creating effective titles for your scientific publications. VideoGIE, 3(9), 260-261.
De La Cruz-Cabanillas, I., & Tejedor-Martínez, C. (2016). The Error Analysis Approach for the Assessment of Automatic Translation. Lingwistyka Stosowana/ Applied Linguistics/ Angewandte Linguistik(16), 1-9. doi:https://www.researchgate.net/publication/287198349_The_Error_Analysis_Approach_for_the_Assessment_of_Automatic_Translation
ElShiekh, A. A. A. (2012). Google translate service: transfer of meaning, distortion or simply a new creation? An investi-gation into the translation process & problems at google. English Language and Literature Studies, 2(1), 56.
George, A. S., & George, A. H. (2023). A review of ChatGPT AI's impact on several business sectors. Partners Universal International Innovation Journal, 1(1), 9-23. doi:DOI:10.5281/zenodo.7644359
Haider, A. S., & Hussein, R. F. (2020). Analysing headlines as a way of downsizing news corpora: Evidence from an Ara-bic–English comparable corpus of newspaper articles. Digital Scholarship in the Humanities, 35(4), 826-844. doi:https://doi.org/10.1093/llc/fqz074
Hartley, T. (2009). Technology and translation. In J. Munday (Ed.), The Routledge companion to translation studies (pp. 120-141). London and New York: Routledge.
Henrickson, L., & Meroño-Peñuela, A. (2023). Prompting meaning: a hermeneutic approach to optimising prompt engi-neering with ChatGPT. AI SOCIETY, 1-16.
Hussein, R. F., Haider, A. S., & Al-Sayyed, S. (2021). A Corpus-Driven Study of Terms Used to Refer to Articles and Methods in Research Abstracts in the Fields of Economics, Education, English Literature, Nursing, and Political Sci-ence. Journal of Educational Social Research, 11(3), 119-131. doi:https://doi.org/10.36941/jesr-2021-0056
Hutchins, J. (2005). Current commercial machine translation systems and computer-based translation tools: system types and their uses. International journal of translation, 17(1-2), 5-38.
Jia, Y., Carl, M., & Wang, X. (2019). How does the post-editing of neural machine translation compare with from-scratch translation? A product and process study. The Journal of Specialised Translation, 31(1), 60-86.
Jiao, W., Wang, W., Huang, J., Wang, X., & Tu, Z. (2023). Is ChatGPT a good translator? Yes with GPT-4 as the engine. arXiv preprint arXiv:2301.08745.
Khoshafah, F. (2023). ChatGPT for Arabic-English translation: Evaluating the accuracy.
Koponen, M. (2010). Assessing machine translation quality with error analysis. Paper presented at the Electronic proceed-ing of the KaTu symposium on translation and interpreting studies.
Koponen, M., & Salmi, L. (2015). On the correctness of machine translation: A machine translation post-editing task. The Journal of Specialised Translation, 23(23), 118-136.
Ledesma, I. B. (2001). Errores y aprendizaje. Paper presented at the Interferencias, cruces y errores.
Popović, M., & Ney, H. (2011). Towards automatic error analysis of machine translation output. Computational Linguis-tics, 37(4), 657-688 doi:https://doi.org/10.1162/COLI_a_00072
Putri, A. T., & Setiajid, H. H. (2021). Instagram Translate and Human Translation In The English Captions Of Jokowi’s Account: An Analysis Of Koponen’s Error Category. Paper presented at the English Language and Literature Interna-tional Conference (ELLiC) Proceedings.
Rusadi, A. M., & Setiajid, H. H. (2023). Evaluating the Accuracy of Google Translate and Chatgpt In Translating Win-dows 11 Education Installation Gui Texts to Indonesian: An Application of Koponen’s Error Category. Paper presented at the English Language and Literature International Conference (ELLiC) Proceedings.
Santos Gargallo, I. (1993). Análisis contrastivo, análisis de errores e interlengua en el marco de la lingüística contrastiva. Madrid.
Son, J., & Kim, B. (2023). Translation Performance from the User’s Perspective of Large Language Models and Neural Machine Translation Systems. Information, 14(10), 574.
Vázquez, G. (1999). Errores?, sin falta! Madrid.
Yilmaz, E. D., Naumovska, I., & Aggarwal, V. A. (2023). AI-Driven Labor Substitution: Evidence from Google Translate and ChatGPT. SSRN. doi:https://ssrn.com/abstract=4400516
Yves, G. (2019). Impact of technology on Translation and Translation Studies. Russian Journal of Linguistics, 23(2), 344-361.
Akasheh, W. M., Haider, A. S., Al-Saideen, B., & Sahari, Y. (2024). Artificial intelligence-generated Arabic subtitles: in-sights from Veed. io's automatic speech recognition system of Jordanian Arabic. Texto Livre, 17, e46952-e46952. doi:10.1590/1983-3652.2024.46952.
Al-Salman, S., & Haider, A. S. (2021). TheRrepresentation of Covid-19 and China in Reuters’ and Xinhua’s Headlines. Search (Malaysia), 13(1), 93-110. doi:https://fslmjournals.taylors.edu.my/wp-content/uploads/SEARCH/SEARCH-2021-13-1/SEARCH-2021-P8-13-1.pdf
Almahasees, Z. (2018). Assessment of Google and Microsoft Bing translation of journalistic texts. International Journal of Languages, Literature and Linguistics, 4(3), 231-235.
Almahasees, Z. (2021). Analysing English-Arabic Machine Translation: Google Translate, Microsoft Translator and Sakhr. London: Routledge.
Almahasees, Z., & Jaccomard, H. (2020). Facebook Translation Service (FTS) Usage among Jordanians during COVID-19 Lockdown. Advances in Science, Technology and Engineering Systems Journal, 5(6), 514-519. doi:10.25046/aj050661
Alrousan, F., & Haider, A. S. (2022). Dubbing television advertisements across cultures and languages: A case study of English and Arabic. Language Value, 15(2), 54-80. doi:https://doi.org/10.6035/languagev.6922
Aydin, Ö. (2023). Google Bard generated literature review: metaverse. Journal of AI, 7(1), 1-14.
Bin Dahmash, N. (2020). ‘I Can't Live Without Google Translate’: A Close Look at the Use of Google Translate App by Second Language Learners in Saudi Arabia. Arab World English Journal (AWEJ) Volume, 11(3), 226-240
Bouguesmia, M. T. (2020). Using AI in Translation, a Technological Leap, or a Translator’s Nightmare. ALTRALANG Journal, 2(02), 78-102.
Bowman, D., & Kinnan, S. (2018). Creating effective titles for your scientific publications. VideoGIE, 3(9), 260-261.
De La Cruz-Cabanillas, I., & Tejedor-Martínez, C. (2016). The Error Analysis Approach for the Assessment of Automatic Translation. Lingwistyka Stosowana/ Applied Linguistics/ Angewandte Linguistik(16), 1-9. doi:https://www.researchgate.net/publication/287198349_The_Error_Analysis_Approach_for_the_Assessment_of_Automatic_Translation
ElShiekh, A. A. A. (2012). Google translate service: transfer of meaning, distortion or simply a new creation? An investi-gation into the translation process & problems at google. English Language and Literature Studies, 2(1), 56.
George, A. S., & George, A. H. (2023). A review of ChatGPT AI's impact on several business sectors. Partners Universal International Innovation Journal, 1(1), 9-23. doi:DOI:10.5281/zenodo.7644359
Haider, A. S., & Hussein, R. F. (2020). Analysing headlines as a way of downsizing news corpora: Evidence from an Ara-bic–English comparable corpus of newspaper articles. Digital Scholarship in the Humanities, 35(4), 826-844. doi:https://doi.org/10.1093/llc/fqz074
Hartley, T. (2009). Technology and translation. In J. Munday (Ed.), The Routledge companion to translation studies (pp. 120-141). London and New York: Routledge.
Henrickson, L., & Meroño-Peñuela, A. (2023). Prompting meaning: a hermeneutic approach to optimising prompt engi-neering with ChatGPT. AI SOCIETY, 1-16.
Hussein, R. F., Haider, A. S., & Al-Sayyed, S. (2021). A Corpus-Driven Study of Terms Used to Refer to Articles and Methods in Research Abstracts in the Fields of Economics, Education, English Literature, Nursing, and Political Sci-ence. Journal of Educational Social Research, 11(3), 119-131. doi:https://doi.org/10.36941/jesr-2021-0056
Hutchins, J. (2005). Current commercial machine translation systems and computer-based translation tools: system types and their uses. International journal of translation, 17(1-2), 5-38.
Jia, Y., Carl, M., & Wang, X. (2019). How does the post-editing of neural machine translation compare with from-scratch translation? A product and process study. The Journal of Specialised Translation, 31(1), 60-86.
Jiao, W., Wang, W., Huang, J., Wang, X., & Tu, Z. (2023). Is ChatGPT a good translator? Yes with GPT-4 as the engine. arXiv preprint arXiv:2301.08745.
Khoshafah, F. (2023). ChatGPT for Arabic-English translation: Evaluating the accuracy.
Koponen, M. (2010). Assessing machine translation quality with error analysis. Paper presented at the Electronic proceed-ing of the KaTu symposium on translation and interpreting studies.
Koponen, M., & Salmi, L. (2015). On the correctness of machine translation: A machine translation post-editing task. The Journal of Specialised Translation, 23(23), 118-136.
Ledesma, I. B. (2001). Errores y aprendizaje. Paper presented at the Interferencias, cruces y errores.
Popović, M., & Ney, H. (2011). Towards automatic error analysis of machine translation output. Computational Linguis-tics, 37(4), 657-688 doi:https://doi.org/10.1162/COLI_a_00072
Putri, A. T., & Setiajid, H. H. (2021). Instagram Translate and Human Translation In The English Captions Of Jokowi’s Account: An Analysis Of Koponen’s Error Category. Paper presented at the English Language and Literature Interna-tional Conference (ELLiC) Proceedings.
Rusadi, A. M., & Setiajid, H. H. (2023). Evaluating the Accuracy of Google Translate and Chatgpt In Translating Win-dows 11 Education Installation Gui Texts to Indonesian: An Application of Koponen’s Error Category. Paper presented at the English Language and Literature International Conference (ELLiC) Proceedings.
Santos Gargallo, I. (1993). Análisis contrastivo, análisis de errores e interlengua en el marco de la lingüística contrastiva. Madrid.
Son, J., & Kim, B. (2023). Translation Performance from the User’s Perspective of Large Language Models and Neural Machine Translation Systems. Information, 14(10), 574.
Vázquez, G. (1999). Errores?, sin falta! Madrid.
Yilmaz, E. D., Naumovska, I., & Aggarwal, V. A. (2023). AI-Driven Labor Substitution: Evidence from Google Translate and ChatGPT. SSRN. doi:https://ssrn.com/abstract=4400516
Yves, G. (2019). Impact of technology on Translation and Translation Studies. Russian Journal of Linguistics, 23(2), 344-361.