Shanghai Journal of Translators ›› 2022, Vol. 165 ›› Issue (4): 35-39.
Previous Articles Next Articles
Received:2021-06-25
Online:2022-07-10
Published:2022-07-28
CLC Number:
| [1] Adriaens, Geert. Simplified English grammar and style correction in an MT framework: The LRE SECC project [J]. Aslib Proceedings, 1995(3) : 78-88. [2] Al Nahas, A.,Tunali,M. S. & Akgul, Y. S. Supervised text style transfer using neural machine translation: Converting between old and modern turkish as an example[DB/OL]. https://www.researchgate.net/publication/335351552. (2021-01-16)[2021-02-10]. [3] Barrón-Cedeño, A. On the mono-and cross-language detection of text reuse and plagiarism[A]. In Fabio Crestani, et al (eds.). Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval,SIGIR 2010[C]. New York:Association for Computing Machinery, 2010: 914-915. [4] Big Think. Here's the innovative writing tool you've been waiting for [EB/OL]. https://bigthink.com/high-culture/whitesmoke-grammar/.(2020-10-20)[2021-01-25]. [5] Bowker, L. & Ciro, J. B. Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community [M]. Emerald: Emerald Group Publishing Limited, 2019. [6] Burchardt, A.,Arle, L.,Vivien M. A new deal for translation quality [J/OL]. Universal Access in the Information Society. https://doi.org/10.1007/s10209-020-00736-5.(2020-07-20)[2020-11-24]. [7] Caswell, I., Liang, B. Recent Advances in Google Translate [EB/OL]. https://www.googblogs.com/recent-advances-in-google-translate/. (2020-06-08)[2021-01-15]. [8] Chon, Y. V., Shin, D. & Kim, G. E. Comparing L2 learners' writing against parallel machine-translated texts: Raters' assessment, linguistic complexity and errors [J]. System, 2021(96): 102-408. [9] Garcia, I., Pena, M. I. Machine translation-assisted language learning: writing for beginners [J]. Computer Assisted Language Learning, 2011(5): 471-487. [10] Jolley, J. R., Maimone, L. Free online machine translation: Use and perceptions by Spanish students and instructors[A]. In Aleidine J. (ed.). Learn Language, Explore Cultures, Transform Lives [C]. Lincoln: University of Nabraska-Lincoln, 2015: 181-200. [11] Lee, M., Briggs N. Effects of using machine translation to mediate the revision process of Korean university students' academic writing[J]. ReCALL, 2021(1): 18-33. [12] Niño, A. Evaluating the use of machine translation post-editing in the foreign language class [J]. Computer Assisted Language Learning, 2008(1): 29-49. [13] Niño, A. Machine translation in foreign language learning: Language learners' and tutors' perceptions of its advantages and disadvantages [J]. ReCALL, 2009(2): 241-258. [14] Niño, A. Exploring the use of online machine translation for independent language learning[J]. Research in Learning Technology, 2020(28): 2402. http://dx.doi.org/10.25304/rlt.v28.2402. (2020-09-04)[2021-03-16]. [15] O'Brien, S., Simard, M., Goulet, M. J. Machine translation and self-post-editing for academic writing support: Quality explorations[A]. In Joss M., Sheila C.,et al (eds.). Translation Quality Assessment:From Principles to Practice[C].Cham: Springer, 2018:237-262. [16] Paris, C.,Vander Linden, K. An interactive support tool for writing multilingual manuals [J]. Computer, 1996 (7): 49-56. [17] Rescigno, A. A., Vanmassenhove, E., Monti, J. & Way, A. A case study of natural gender phenomena in translation: A comparison of Google Translate, Bing Microsoft Translator and DeepL for English to Italian, French and Spanish[A]. In Johanna M., et al(eds.). Proceedings of the Seventh Italian Conference on Computational Linguiistics CLiC-it[C]. Bologna:Technical University of Aache, 2020: 359-364. [18] Rogerson, A. M., McCarthy, G. Using internet based paraphrasing tools: Original work, patchwriting or facilitated plagiarism? [J]. Internaptional Journal for Educational Integrity, 2017, (1): 1-15. [19] Stapleton, P., Kin, B. L. K. Assessing the accuracy and teachers' impressions of Google Translate: A study of primary L2 writers in Hong Kong [J]. English for Specific Purposes, 2019(56): 18-34. [20] Treece, R. “Yo Lata Mosca Espalda”: Student compositions and online translators[A]. In L.Gómez Chova,et al (eds.). INTED2011 Proceedings [C]. Valencia:IATED, 2011: 6410-6414. [21] Tsai, S. C. Using google translate in EFL drafts: A preliminary investigation [J]. Computer Assisted Language Learning, 2019(5-6): 510-526. [22] Tsai, S. C. Chinese students' perceptions of using Google Translate as a translingual CALL tool in EFL writing [J].Computer Assisted Language Learning, 2020(7): 1-23. [23] White, M., Rozovskaya, A. A comparative study of synthetic data generation methods for grammatical error correction [A]. In Jill Burstein et al (eds.). Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications[C]. Seattle: Association for Computational Linguistics, 2020: 198-208. [24] Xu, J. Machine translation for editing compositions in a Chinese language class: Task design and student beliefs [J]. Journal of Technology and Chinese Language Teaching, 2020(1):1-18. [25] Zhou, J., Li, C., Liu, H., et al. Chinese grammatical error correction using statistical and neural models [A]. In Zhang,M., Ng,V. et al (eds.). Natural Language Processing and Chinese Computing.NLPCC 2018[C]. Cham :Springer, 2018: 117-128. [26] Zhu, J., Xia, Y., Wu, L., et al. Incorporating bert into neural machine translation [DB/OL]. https://arxiv.org/abs/2002.06823.(2020-02-17)[2021-2-11]. [27] 冯全功,崔启亮.译后编辑研究:焦点透析与发展趋势[J]. 上海翻译,2016(6):67-74. [28] 郭望皓,范江威,张克亮. 融合语言学知识的神经机器翻译研究进展[J]. 计算机科学与探索. 2021,15(7):1183-1194. [29] 何绍荣. 基于互信息和关系积理论的特征选择方法[J]. 计算机工程,2010(13): 257-259. |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||
