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Original Article | Volume 2 Issue 4 (ACR, 2025) | Pages 2666 - 2674
Bridging Language Barriers in Education and Industry through AI and Real-Time Translation Technologies
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Designation: Professor, Department:- Management Studies, Institute:- Amritsar Group of Colleges, District:- Amritsar, City:- Amritsar, State:- Punjab
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Designation: Area Chair-Associate Professor, Department: Business Communication, Institute: Management Development Institute Murshidabad,West Bengal, District: Murshidabad, City: Raghunathganj, State:West Bengal
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Designation: Assistant professor, Institution/Organization Name: International Institute of Business Studies
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Professor, Royal School of Languages, The Assam Royal Global University
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Department of History, Designation: Assistant Professor, Institute Jogesh Chandra Chaudhuri College, State: West Bengal, City Kolkata
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Abstract

Also in a fast enlarging world, language dissimilarity has remained an enormous obstacle preventing inclusive communication, cooperation and education. This work explores the main idea of how real-time translation and technologies based on Artificial Intelligence (AI) can effectively broker linguistic gaps in two highly important areas education and industry. Through two-method research design, comprising the system appraisal and application in the industry in terms of real-time applications of neural machine translation (NMT), natural language processing (NLP) and voice recognition systems, this study examines the efficiency of real-time application of networks of neural machine translation (NMT), natural language processing (NLP) as well as voice recognition systems in a multilingual setting. Indian, German, and Kenyan learning places and Japanese, Brazilian, and UAE working environments were analyzed to determine the viability of deployment, precision, and user enjoyability. Engines, such as Google Translate API, DeepL, and open protein models, such as MarianMT were compared in 14 languages, based on BLEU degree, latency, and maintained contextual integrity. In the field of education, AI tools opened the possibility of a real-time multilingual lecture, collaborative assignments, and inclusive evaluation of learners with different linguistic backgrounds. The same technologies facilitated effective cross-functional collaboration and safety training at industry, and customer service within the multilingual supply chains. Although an increment in productivity and inclusivity was identified, accent sensitivity, the loss of contextual nuance, and ethical data privacy issues appeared. The results provide a good demonstration of the potential changes that AI-based translation systems can create, as well as outline the necessity of culturally cognizant, privacy-friendly deployment paradigms. This paper provides its contribution to the topic of digital inclusion, which is becoming increasingly popular delight as a catalyst of a fully global workforce and education

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