Study on the Corpus of Bilingual Translators Training Model during the Covid-19 Pandemic
Abstract
research utilized scientometric analysis and examined literature sourced from the Web of Science (WoS) core collection and the China National Knowledge Infrastructure (CNKI) spanning from 2019 to 2023. The main aim was to explore the present state of the bilingual (English and
Chinese) translators training model and to identify the future trends in corpus development. The findings offer valuable insights for scholars
to delve deeper into this area of study.
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[1] Abdul-Mageed, M., A. R. Elmadany, E. M. B. Nagoudi, D. Pabbi, K. Verma, and R. Lin. 2021. Mega-COV: A Billion-Scale Dataset of 100+ Languages for COVID-19. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 340220, Online. Association for Computational Linguistics. 10.18653/v1/2021.eacl-main.298. Search in Google Scholar
[2] Chen, C. (2017). Science mapping: a systematic review of the literature. Journal of Data and Information Science, 2(2), 140.
[3] Chen, Y. (2018). The Application of Task-based Teaching Method in Higher Vocational English Teaching. Journal of Liaoning Higher Vocational, 20 (8), 44-46.
[4] Chen, C., Hu, Z., Liu, S., & Tseng, H. (2012). Emerging trends in regenerative medicine: a scientometric analysis in CiteSpace. Expert Opinion on Biological Therapy, 12(5), 593608.
[5] Ellis, R. (2016). Focus on form: a critical review. Language Teaching Research, 20(3), 405428.
[6] Kasper?, R. and Motiej?nien?, J. (2021). Impacts of global pandemic on translators career and translator training. Current Trends in Translation Teaching and Learning E, 8, 154 195. https://doi.org/10.51287/cttle 20216
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