A Comparative Analysis of Translation Quality in Scientific and Technical Texts from the Perspective of Eco-Translatology: Taking Deep Seek Translation and Human Translation as Examples

Hairong Liao

doi:10.54097/bzb27z81

Authors

Hairong Liao

DOI:

https://doi.org/10.54097/bzb27z81

Keywords:

Deep Seek, Eco-Translatology, human-machine translation comparison, human-machine collaboration, scientific and technical translation.

Abstract

Based on the Three-Dimensional Transformation Theory (linguistic dimension, cultural dimension, and communicative dimension) of Eco-Translatology, this study conducts a comparative analysis of the quality differences between Deep Seek and human translations of scientific and technical texts. The research selects several scientific and technical articles from The Economist as objects of study and compares the two translation versions in terms of terminology accuracy, fluency, and cultural adaptability. The results indicate that Deep Seek demonstrates advantages in terminology accuracy and standardized text processing, but still falls short of human translation in handling cultural-loaded words and maintaining logical coherence. Furthermore, the study explores potential career pathways for foreign language learners in the AI era, providing valuable insights and suggestions for their professional development.

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References

[1] Hongwei Chen and Yadan Li. A Course in Chinese-English Translation (Book style). Shanghai: Shanghai Foreign Language Education Press, 2018, p. 207.

[2] Shuang Dong. “Research on Scientific Text Translation Under Functional Equivalence Theory: A Case Study Comparing Google Translate and Human Translation” (Periodical style). Brand, no. 02, p. 128, 2015.

[3] Yonglin Fu and Yueqin Tang. Science and Technology Translation (Book style). Beijing: Foreign Language Teaching and Research Press, 2011, pp. 2–30, 112.

[4] Gengshen Hu. “Viewing Translation Theory Through Terminology: An Overview of the Adaptation and Selection Approach to Translation" (Periodical style). Shanghai Journal of Translators, no. 02, pp. 1–5, 2008.

[5] Gengshen Hu. “Research Focus and Theoretical Perspectives of Eco-Translatology” (Periodical style). Chinese Translators Journal, vol. 32, no. 02, pp. 5–9, 95, 2011.

[6] Zhonghua Lei. “A New Wave of Challenges Facing Translation Programs and Countermeasures”. Beijing: Beijing Language and Culture University, 2025. [Online]. Available: https://mp.weixin.qq.com/s/SGZoHQF5IFfC70vNAZwcgw

[7] Fengqi Li. “A Comparative Study on Machine vs. Human Translation Quality in English-Chinese Translation in the Era of Artificial Intelligence” (Periodical style). Foreign Language World, no. 04, pp. 72–79, 2022.

[8] Yan Li and Xinyuan Qi. “Transformation and Innovative Development Paths of the Translation Industry Under Human-Machine Collaboration” (Periodical style). Technology Enhanced Foreign Language Education, no. 02, pp. 31–36, 46, 101, 2025.

[9] Junying Liang and Yiguang Liu. “The Advantage of Human Intelligence in Translation Competence: A Corpus-Based Comparative Study of Human and Machine Translation” (Periodical style). Foreign Languages and Their Teaching, no. 03, pp. 74–84, 147–148, 2023.

[10] Jiaqi Liu. “Key Points in Translating Scientific Texts on Automotive Part Casting: An English-Chinese Perspective” (Periodical style). Special Casting & Nonferrous Alloys, vol. 43, no. 03, pp. 438–439, 2023.

[11] Wei Zhang. “Challenges and Prospects for Translation Programs in the AI Era: Analysis Based on a Large-Scale Social Survey” (Periodical style). Chinese Translators Journal, vol. 45, no. 05, pp. 139–148, 2024.

[12] Guofeng Zheng and Xi Pan. “Terminology Machine Translation in the Era of Artificial Intelligence: Challenges and Prospects” (Periodical style). Foreign Languages in China, vol. 22, no. 04, pp. 96–104, 2025.