NLP for professional english proficiency in spanish-speaking contexts

Authors

https://doi.org/10.22105/metaverse.v2i2.72

Abstract

As globalization reshapes professional communication, Business English proficiency has become an essential skill for professionals in Spanish-speaking markets. However, traditional language instruction often prioritizes grammatical accuracy over practical communicative competence, leaving learners unprepared for the demands of real-world business interactions. This paper explores how Natural Language Processing (NLP) tools—including AI-driven writing assistants, automated speech recognition, and adaptive learning platforms—can bridge this gap by offering personalized, context-aware, and interactive learning experiences adapted to professional needs. To illustrate the impact of NLP on Business English instruction, we present case studies from the University of Valladolid. The students were studying Business English in the second year of Commerce and we followed a methodology for teaching this subject that has integrated NLP-based technologies into their curricula. These case studies highlight how AI-powered tools such as Grammarly, ChatGPT, and speech recognition software enhance written and spoken proficiency through real-time feedback, error correction, and contextual vocabulary expansion. Additionally, chatbot-based simulations provide learners with opportunities to practice professional negotiations, email correspondence, and presentations in an AI-assisted environment, fostering confidence and fluency. Findings indicate that that NLP-driven learning methods significantly improve learners' engagement and real-world application of Business English. However, challenges remain, including the need for localized NLP models, potential biases in AI feedback, and the balance between technology and human instruction. The paper discusses strategies to mitigate these issues while maximizing the benefits of NLP in language education. By moving beyond grammar toward practical business communication, NLP has the potentital to transform how Spanish speaking professionals acquire and apply Englsih language skills.

Keywords:

Business english, NLP-driven learning method, Spanish context

References

  1. [1] Bailey, D., & Lee, A. R. (2020). An exploratory study of Grammarly in the language learning context: An analysis of test-based, textbook-based and Facebook corpora. https://arxiv.org/abs/2111.04455

  2. [2] Indurkhya, N., & Damerau, F. J. (2010). Handbook of natural language processing. Chapman and Hall/CRC. https://doi.org/10.1201/9781420085938

  3. [3] Zhai, C., & Massung, S. (2016). Text data management and analysis: A practical introduction to information retrieval and text mining. Morgan & Claypool. https://dl.acm.org/doi/book/10.1145/2915031

  4. [4] Loughnane, R., McCurdy, K., Kolb, P., & Selent, S. (2017). Linked data for language-learning applications. Proceedings of the 12th workshop on innovative use of nlp for building educational applications (pp. 44–51). Association for Computational Linguistics. https://doi.org/10.18653/v1/W17-5005

  5. [5] Giray, L. (2024). “Don’t let Grammarly overwrite your style and voice:” Writers’ advice on using Grammarly in writing. Internet reference services quarterly, 28(3), 293–303. https://doi.org/10.1080/10875301.2024.2344762

  6. [6] Al Balushi, K. (2025). Using AI-powered grammar correction tools to support ESL students’ writing skills development. In Optimizing research techniques and learning strategies with digital technologies (pp. 319–334). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-7863-2.ch012

  7. [7] Ghannam, M. H., Alwan, A., Shamsan, B. T., Abdullah, A., Ameen, E., Hassan, A., … & Rashed, B. A. (2025). Investigating of AI tools’ enhancement on the english writing skills among non-native speakers. Journal of social studies, 31(3). https://doi.org/10.20428/jss.v31i3.2731

  8. [8] Haider, K. (2024). Natural language processing in AI-powered systems: Techniques and future prospects. Journal of ai range, 1(1), 40–53. https://www.researchcorridor.org/index.php/jair/article/view/267

  9. [9] salvador, K. A. (2024). AI-mediated communication in academic organizations: Issues and directions. Southeast Asian media studies, 6(1), 66. https://B2n.ir/hj6225

  10. [10] Ndububa, C. L. (2025). Challenges in teaching english speech sounds to non-native speakers using british dictionaries. International journal of academic pedagogical research (IJAPR), 9(4), 74–86. https://B2n.ir/xy4634

  11. [11] Mehta, S. N., Roth, A., Munteanu, C., & Chandna, S. (2025). AI-based pronunciation assessment and grammatical error correction with feedback for the german language. International conference on human-computer interaction (pp. 388–407). Springer. https://doi.org/10.1007/978-3-031-93415-5_23

  12. [12] Chen, X., Li, J., & Ye, Y. (2024). A feasibility study for the application of AI-generated conversations in pragmatic analysis. Journal of pragmatics, 223, 14–30. https://doi.org/10.1016/j.pragma.2024.01.003

  13. [13] Falcão Filho, H. A. (2024). Making sense of negotiation and AI: The blossoming of a new collaboration. International journal of commerce and contracting, 8(1–2), 44–64. https://doi.org/10.1177/20555636241269270

  14. [14] Blodgett, S. L., Barocas, S., Daumé III, H., & Wallach, H. (2020). Language (Technology) is power: A critical survey of" bias" in NLP. https://arxiv.org/abs/2005.14050

  15. [15] Liu, G. L., Lee, J. S., & Zhao, X. (2025). Critical digital literacies, agentic practices, and AI-mediated informal digital learning of english. System, 134, 103797. https://doi.org/10.1016/j.system.2025.103797

  16. [16] Ramesh, K., Sitaram, S., & Choudhury, M. (2023). Fairness in language models beyond English: Gaps and challenges. https://arxiv.org/abs/2302.12578

  17. [17] Moreno, R. G., & Sznajder, H. S. (2013). Business communication across three European cultures: A contrastive analysis of British, Spanish and Polish email writing. Ibérica, (26), 77–98. http://www.revistaiberica.org/index.php/iberica/article/view/274

  18. [18] Golijanin, K. (2023). Directness and indirectness in cross-cultural communication [Thesis]. https://repozitorij.ffst.unist.hr/islandora/object/ffst:4153

  19. [19] Clyne, M. G., Norrby, C., & Warren, J. (2009). Language and human relations: Styles of address in contemporary language. Cambridge University Press. https://B2n.ir/eb4097

  20. [20] Vives, A. (2022). Social and environmental responsibility in small and medium enterprises in Latin America. In Corporate citizenship in latin america: new challenges for business (pp. 39–50). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9781351288484-6/social-environmental-responsibility-small-medium-enterprises-latin-america-antonio-vives

Published

2025-06-14

How to Cite

Garcés García, P. . (2025). NLP for professional english proficiency in spanish-speaking contexts. Metaversalize, 2(2), 79-93. https://doi.org/10.22105/metaverse.v2i2.72

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