Journal of Language Service Studies

Publisher Name Change Notice: Starting in 2026, all journals and manuscripts will be published under the new publisher name Nature and Information Engineering Publishing Sdn. Bhd.

Language Service Studies in the Era of AI: Development and Prospects

Authors

  • Can Cui

    College of Foreign Languages, Capital Normal University, Beijing 100089, China

    Author
  • Yue Chai

    College of Foreign Languages, Capital Normal University, Beijing 100089, China

    Author

DOI:

https://doi.org/10.63385/jlss.v1i2.136

Keywords:

Language Services, Artificial Intelligence, Industry Developments

Abstract

With the rapid advancement of artificial intelligence (AI), the field of language service studies has ushered in a paradigm shift and holds broad development prospects in the AI era. This paper first systematically reviews the global and domestic research progress in AI-driven language services: internationally, scholars focus on the integration of AI technologies with language service workflows, efficiency optimization, and quality evaluation; domestically, research leans toward addressing practical needs such as cross-cultural communication under national strategies and the localization of AI language tools. Subsequently, it examines the current applications of AI in the language service domain, covering key technologies including neural machine translation (NMT) with enhanced contextual adaptation, speech recognition and synthesis supporting real-time multilingual interaction, and large language models (LLMs) enabling intelligent content creation and multi-modal language services. Finally, the paper envisions future research directions such as cross-disciplinary integration of AI, linguistics, and communication, ethical governance of AI language services, and personalized service innovation. It further puts forward pertinent suggestions, including strengthening the construction of multilingual corpus resources, improving the evaluation system for AI-driven language services, and cultivating interdisciplinary talents, so as to promote the high-quality development of the global language service industry.

References

[1]Wang, L.F., 2021. Marching from a Large Country to a Strong One in Language Services——Revisiting Language Services, Language-service Discipline, and Language-service Talents. Journal of Beijing International Studies University. 43(1), 3–11. (in Chinese)

[2]Chen, C., 2004. Searching for intellectual turning points: Progressive knowledge domain visualization. PNAS. 101(1), 5303–5310. DOI: https://doi.org/10.1073/pnas.0307513100

[3]Killman, J., 2024. Machine translation literacy in the legal translation context: A SWOT analysis perspective. Interpreter and Translator Trainer. 18(2), 271–289. DOI: https://doi.org/10.1080/1750399X.2024.2344282

[4]Sakamoto, A., 2019. Unintended consequences of translation technologies: From project managers’ perspectives. Perspectives: Studies in Translation Theory and Practice. 27(1), 58–73. DOI: https://doi.org/10.1080/0907676X.2018.1473452

[5]Turner, A.M., Choi, Y.K., Dew, K., et al., 2019. Evaluating the usefulness of translation technologies for emergency response communication: A scenario-based study. JMIR Public Health Surveill. 5(1), e11171. DOI: https://doi.org/10.2196/11171

[6]Urzedo, D., Sworna, Z.T., Hoskins, A.J., et al., 2024. AI chatbots contribute to global conservation injustices. Humanities & Social Sciences Communications. 11(1), 204. DOI: https://doi.org/10.1057/s41599-024-02720-3

[7]Granell, X., Chaume, F., 2023. Audiovisual translation, translators, and technology: From automation pipe dream to human-machine convergence. Linguistica Antverpiensia, New Series—Themes in Translation Studies. 22, 20–40. DOI: https://doi.org/10.52034/lans-tts.v22i.776

[8]Pang, J.H., Yang, B.S., Wong, D.F., et al., 2023. Rethinking the exploitation of monolingual data for low-resource neural machine translation. Computational Linguistics. 50(1), 25–47. DOI: https://doi.org/10.1162/coli_a_00496

[9]Quinci, C., 2024. The impact of machine translation on the development of info-mining and thematic competences in legal translation trainees: A focus on time and external resources. Interpreter and Translator Trainer. 18(2), 290–312. DOI: https://doi.org/10.1080/1750399X.2024.2344285

[10]Alotaibi, H., Salamah, D., 2023. The impact of translation apps on translation students’ performance. Education and Information Technologies. 28(8), 10709–10729. DOI: https://doi.org/10.1007/s10639-023-11578-y

[11]Prieto Ramos, F., 2024. Revisiting translator competence in the age of artificial intelligence: The case of legal and institutional translation. Interpreter and Translator Trainer. 18(2), 148–173. DOI: https://doi.org/10.1080/1750399X.2024.2344942

[12]Venkatesan, H., 2023. Technology preparedness and translator training. Babel—International Journal of Translation. 69(5), 666–703. DOI: https://doi.org/10.1075/babel.00335.ven

[13]Hassan, H., Aue, A., Chen, C., et al., 2018. Achieving human parity on automatic Chinese to English news translation. arXiv preprint. arXiv:1803.05567. DOI: https://doi.org/10.48550/arXiv.1803.05567

[14]Sharma, V.K., Mittal, N., Vidyarthi, A., 2023. Semantic morphological variant selection and translation disambiguation for cross-lingual information retrieval. Multimedia Tools and Applications. 82(6), 8197–8212. DOI: https://doi.org/10.1007/s11042-021-11074-w

[15]Qin, F.Z., 2020. Interpretation of the Application of AI Speech Transcription Technology in Conferences. Electronics World. (22), 190–191. DOI: https://doi.org/10.19353/j.cnki.dzsj.2020.22.084 (in Chinese)

[16]Li, K.H., Jiang, S., 2020. Machine Learning and Cultural Production Reform: From the Perspective of AI Technology Development. Journal of Xiangtan University (Philosophy and Social Sciences Edition). 44(1), 74–79. DOI: https://doi.org/10.13715/j.cnki.jxupss.2020.01.012 (in Chinese)

[17]Hu, K.B., Li, X.Q., 2023. Development of Translation Studies in the Context of Large Language Models: Issues and Prospects. Chinese Translators Journal. 44(6), 64–73. Available from: https://corpus.shisu.edu.cn/bd/9b/c9380a179611/page.htm (in Chinese)

[18]Zhao, L.X., Yang, J., 2021. Indonesian Speech Synthesis Based on BERT Pre-trained Language Model. Journal of Yunnan University (Natural Sciences Edition). 43(6), 1086–1095. (in Chinese)

[19]Qi, S.Y., Hu, H.Y., Li, H.B., et al., 2024. Domain-Specific Question Answering System Construction Approach Integrated with Large Language Model. Journal of Beijing University of Posts and Telecommunications. 47(4), 50–56. DOI: https://doi.org/10.13190/j.jbupt.2023-279 (in Chinese)

[20]Feng, Z.W., Zhang, D.K., Rao, G.Q., 2023. From Turing Test to ChatGPT: A Milestone of Man-Machine Interaction and Its Enlightenment. Chinese Journal of Language Policy and Planning. 8(2), 20–24. DOI: https://doi.org/10.19689/j.cnki.cn10-1361/h.20230202 (in Chinese)

[21]Feng, T., Qu, L., Tandon, N., et al., 2025. On the reliability of large language models for causal discovery. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, Vienna, Austria, 27 July–1 August 2025; pp. 4210–4225. DOI: https://doi.org/10.18653/v1/2025.acl-long.471

[22]Wang, Z., 2024. Causal Bench: A comprehensive benchmark for evaluating causal reasoning capabilities of large language models. In Proceedings of the 10th SIGHAN Workshop on Chinese Language Processing (SIGHAN-10), Bangkok, Thailand, 16 August 2024; pp. 189–201. DOI: https://doi.org/10.18653/v1/2024.sighan-1.17

[23]Cui, Q.L., 2025. Development Trends of Language Services Industry in the Era of Artificial Intelligence. Journal of Beijing International Studies University. 47(1), 62–72. DOI: https://doi.org/10.12002/j.bisu.565 (in Chinese)

[24]Al-Tarawneh, A., Abu Hatab, W., Al-Badawi, M., 2025. Artificial intelligence and the transformation of human translation: A study of the translation industry in Jordan. Cogent Arts & Humanities. 12(1), 2598659. DOI: https://doi.org/10.1080/23311983.2025.2598659

[25]Wang, C., Zou, B., 2025. D-ID Studio: Empowering language teaching with AI avatars. TESOL Journal. 16(2), e70034. DOI: https://doi.org/10.1002/tesj.70034

[26]Miranda, S., Vegliante, R., 2025. Leveraging AI-generated virtual speakers to enhance multilingual e-learning experiences. Information. 16(2), 132. DOI: https://doi.org/10.3390/info16020132

Downloads

How to Cite

Cui, C., & Chai, Y. (2025). Language Service Studies in the Era of AI: Development and Prospects. Journal of Language Service Studies, 1(2), 33–48. https://doi.org/10.63385/jlss.v1i2.136