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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 杜憶萍 | zh_TW |
| dc.contributor.advisor | I-Ping Tu | en |
| dc.contributor.author | 陳玟瑾 | zh_TW |
| dc.contributor.author | Wen-Chin Chen | en |
| dc.date.accessioned | 2024-08-29T16:13:18Z | - |
| dc.date.available | 2024-08-30 | - |
| dc.date.copyright | 2024-08-29 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-15 | - |
| dc.identifier.citation | [1] 清国人日本留学生の言語文化接触 相互誤解の日中教育文化交流, ひつじ房, 2010.
[2] I. G. A. M. Agung, P. Budiartha, and N. Suryani. Translation performance of google translate and deepl in translating indonesian short stories into english. 01 2024. [3] M.Aiken.Anupdatedevaluationofgoogletranslateaccuracy.StudiesinLinguistics and Literature, 3:p253, 07 2019. [4] M. W. Aiken. An analysis of google translate accuracy. 2012. [5] M. W. Aiken, M. Park, L. L. Simmons, and T. Lindblom. Automatic translation in multilingual electronic meetings. 2010. [6] H. Aldawsari. Comparing the performance of google translate and systran on arabic lexical ambiguity. Arab World English Journal For Translation and Literary Studies, 7:19–34, 08 2023. [7] R.Anil,A.Dai,O.Firat,M.Johnson,D.Lepikhin,A.Passos,S.Shakeri,E.Taropa, P. Bailey, Z. Chen, E. Chu, J. Clark, L. Shafey, Y. Huang, K. Meier-Hellstern, G. Mishra, E. Moreira, M. Omernick, and K. Robinson. Palm 2 technical report, 05 2023. [8] E. M. Balk, M. Chung, N. Hadar, K. Patel, W. W. Yu, T. A. Trikalinos, and L. K. W. Chang. Accuracy of data extraction of non-english language trials with google translate. 2012. [9] X. Chen, S. Acosta, and A. Barry. Evaluating the accuracy of google translate for diabetes education material. JMIR Diabetes, 1:e3, 06 2016. [10] A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, P. Schuh, K. Shi, S. Tsvyashchenko, J. Maynez, A. Rao, P. Barnes, Y. Tay, N. Shazeer, V. Prabhakaran, E. Reif, N. Du, B. Hutchinson, R. Pope, J. Bradbury, J. Austin, M. Isard, G. Gur-Ari, P. Yin, T. Duke, A. Levskaya, S. Ghemawat, S. Dev, H. Michalewski, X. Garcia, V. Misra, K. Robin- son, L. Fedus, D. Zhou, D. Ippolito, D. Luan, H. Lim, B. Zoph, A. Spiridonov, R. Sepassi, D. Dohan, S. Agrawal, M. Omernick, A. M. Dai, T. S. Pillai, M. Pel- lat, A. Lewkowycz, E. Moreira, R. Child, O. Polozov, K. Lee, Z. Zhou, X. Wang, B. Saeta, M. Diaz, O. Firat, M. Catasta, J. Wei, K. Meier-Hellstern, D. Eck, J. Dean, S. Petrov, and N. Fiedel. Palm: Scaling language modeling with pathways. J. Mach. Learn. Res., 24:240:1–240:113, 2023. [11] D. Coughlin. Correlating automated and human assessments of machine translation quality. Proceedings of MT Summit IX, 01 2001. [12] C. Culy and S. Riehemann. The limits of n-gram translation evaluation metrics. 11 2003. [13] T. Fishman. “we know it when we see it”is not good enough: toward a standard definition of plagiarism that transcends theft, fraud, and copyright. 2009. [14] T. Foltýnek, N. Meuschke, and B. Gipp. Academic plagiarism detection: A systematic literature review. ACM Comput. Surv., 52(6), oct 2019. [15] J. Jackson, A. Kuriyama, A. Anton, A. Choi, J. Fournier, A. Geier, F. Jacquerioz, D. Kogan, C. Scholcoff, and R. Sun. The accuracy of google translate for abstracting data from non-english-language trials for systematic reviews. Annals of internal medicine, 171(9):677–679, Nov. 2019. [16] R. R. Khanna, L. S. Karliner, M. Eck, E. Vittinghoff, C. J. Koenig, and M. C. Fang. Performance of an online translation tool when applied to patient educational mate- rial. Journal of Hospital Medicine, 6(9):519–525, Oct 2011. [17] G.-Z. Liu. 防治學生英文寫作抄襲之認知與方法探究:以二所研究型大學為 例. 英語教學期刊 (THCI Core), 36(4), Dec. 2012. THCI Core. [18] K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu. Bleu: a method for automatic evaluation of machine translation. In P. Isabelle, E. Charniak, and D. Lin, editors, Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pages 311–318, Philadelphia, Pennsylvania, USA, July 2002. Association for Computational Linguistics. [19] S.PatilandP.Davies.Useofgoogletranslateinmedicalcommunication:Evaluation of accuracy. BMJ: British medical journal, 349:g7392, 12 2014. [20] M. Prates, P. Avelar, and L. Lamb. Assessing gender bias in machine translation: a case study with google translate. Neural Computing and Applications, 32, 05 2020. [21] A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin. Attention is all you need, Dec 2017. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95130 | - |
| dc.description.abstract | 隨著翻譯的需求與日俱增,各種翻譯軟體如雨後春筍般湧現。時逢論文抄襲爭議層出不窮,因此許多學校發布新的相關規定來因應,要求在提交論文前需通過指定的論文相似度檢測。若有人利用翻譯軟體將他人的論文經過多層翻譯後,當作自己的論文,則如何評估翻譯的表現也因此成為了一個重要的議題。在眾多案例中,中國蘇州大學社會學院的學生邵寶在其博士論文《清末留日學生與日本社會》中,在未引用或標注來源的情況下將日本學者酒井順一郎的著作翻譯至中文後直接使用,相似比例達到其論文的80%,而我們決定採用其中翻譯相似的概念,以翻譯軟體生成不同版本的譯本後,再透過論文比對系統來評估該翻譯軟體的表現。
在本論文中,我們會瞭解檢測翻譯表現這個領域的發展現況,並以100篇英文論文為我們的資料。我們將論文相似度比對系統Turnitin作為檢測Google翻譯軟體表現的工具,來分析牽涉到中文、日文、法文和德文的翻譯中不同的翻譯方式對論文相似度的影響,包括單層翻譯和雙層翻譯。結果顯示出翻譯方式對論文相似度具有顯著影響,其中牽涉到日文的翻譯表現較差,而牽涉到中文的翻譯表現較佳。 | zh_TW |
| dc.description.abstract | With the increasing demand for translation, various translation software has emerged rapidly. Amidst ongoing plagiarism controversies, many universities have implemented new regulations requiring theses to pass designated similarity checks before submission. If someone uses translation software to translate another person's paper multiple times and then presents it as their own, evaluating the performance of such translations becomes a critical issue. A notable case is that of Shao Bao, a student at the School of Sociology at Soochow University in China, who translated and used approximately 80% of Japanese scholar Sakai Junichiro's work "Qing Dynasty Chinese Students in Japan and Language and Culture Contact" in his doctoral dissertation without proper citation. Based on this case, we adopt the concept of translation similarity by using translation software to generate different versions of translations and then using a thesis similarity detection system to evaluate the accuracy of the translation software.
This study explores the current state of translation accuracy evaluation, using 100 English academic papers as the dataset. Turnitin, the similarity detection system is employed to assess the performance of Google Translate, analyzing the impact of different translation methods—single-layer and double-layer translations—on thesis similarity across Chinese, Japanese, French, and German translations. The results indicate that translation methods significantly affect thesis similarity, with translations involving Japanese performing worse and those involving Chinese performing better. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-29T16:13:18Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-08-29T16:13:18Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 摘要 2
Abstract 3 目次 5 圖次 7 表次 8 第一章 緒論 1 1.1 研究背景與動機............................. 1 1.2 Turnitin之選取與簡介.......................... 2 1.3 Google翻譯之選取與簡介........................ 3 1.4 論文架構................................. 6 第二章 文獻回顧 8 第三章 資料選取與處理 14 3.1 資料處理................................. 14 3.2 資料生成................................. 15 3.3 報告結果與數值選取 .......................... 16 第四章 資料分析 20 4.1 資料部分展示 .............................. 20 4.2 資料分析................................. 21 4.2.1 離群值 ................................ 21 4.2.2 箱形圖 ................................ 22 4.2.3 密度圖 ................................ 23 4.2.4 集群分析...................26 第五章 結論 32 參考文獻 33 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 翻譯表現評估 | zh_TW |
| dc.subject | 翻譯表現 | zh_TW |
| dc.subject | Turnitin(相似度比對系統) | zh_TW |
| dc.subject | Turnitin (Similarity checking system) | en |
| dc.subject | Translation performance | en |
| dc.subject | Evaluation of translation performance | en |
| dc.title | 評估 Google 翻譯表現 —以 4 種語言翻譯 100 篇英文論文為例 | zh_TW |
| dc.title | Evaluating the Performance of Google Translation —For 4 languages on 100 English written papers | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳定立;章為皓;姚怡慶;鍾思齊 | zh_TW |
| dc.contributor.oralexamcommittee | Ting-Li Chen;Wei-Hau Chang;Yi-Ching Yao;Szu-Chi Chung | en |
| dc.subject.keyword | 翻譯表現,翻譯表現評估,Turnitin(相似度比對系統), | zh_TW |
| dc.subject.keyword | Translation performance,Evaluation of translation performance,Turnitin (Similarity checking system), | en |
| dc.relation.page | 35 | - |
| dc.identifier.doi | 10.6342/NTU202404301 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-08-16 | - |
| dc.contributor.author-college | 理學院 | - |
| dc.contributor.author-dept | 應用數學科學研究所 | - |
| 顯示於系所單位: | 應用數學科學研究所 | |
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