AI-Powered Language Translation for Low-Resource Languages
Abstract
This paper presents a comprehensive technical framework for AI-powered language translation tailored specifically for low-resource languages. Our approach addresses the severe data scarcity issues by integrating transfer learning, multilingual pre-training, and domain adaptation into a unified neural machine translation (NMT) architecture. We mathematically formalize the translation process as a probabilistic sequence-to-sequence problem, expressed as
References
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” Advances in Neural Information Processing Systems (NeurIPS), vol. 30, pp. 5998 6008, 2017.
D. Bahdanau, K. Cho, and Y. Bengio, “Neural machine translation by jointly learning to align and translate,” International Conference on Learning Representations (ICLR), 2015. 19
R. Sennrich, B. Haddow, and A. Birch, “Neural machine translation of rare words with subword units,” Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 1715–1725, 2016.
M. Johnson, M. Schuster, Q. Le, Y. Krikun, Y. Wu, Z. Chen, N. Thorat, F. Viégas, M. Wattenberg, G. Corrado, and J. Dean, “Google’s multi lingual neural machine translation system: Enabling zero-shot trans lation,” Transactions of the Association for Computational Linguistics (TACL), vol. 5, pp. 339–351, 2017.
A. Conneau, G. Lample, M. Ranzato, L. Denoyer, and H. Jégou, “Word translation without parallel data,” International Conference on Learn ing Representations (ICLR), 2018.
G. Lample, A. Conneau, L. Denoyer, and M. Ranzato, “Unsupervised machine translation using monolingual corpora only,” International Conference on Learning Representations (ICLR), 2018.
H. Schwenk and X. Li, “A challenge for neural machine translation: Do main adaptation,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018, pp. 2800 2810.
A. Conneau, K. Khandelwal, N. Goyal, V. Chaudhary, G. Wenzek, F. Guzmán, E. Grave, M. Ott, L. Zettlemoyer, and V. Stoyanov, “Unsu pervised cross-lingual representation learning at scale,” Proceedings of the 58th Annual Meeting of the Association for Computational Linguis tics (ACL), pp. 844–857, 2020.
P. Koehn and R. Knowles, “Six challenges for neural machine transla tion,” in Proceedings of the First Workshop on Neural Machine Trans lation, 2017, pp. 28–39.
M. Ott, S. Edunov, D. Grangier, and M. Auli, “Scaling neural machine translation,” Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1–12, 2018.
G. Neubig, “Neural machine translation and sequence-to-sequence mod els: A tutorial,” Journal of Machine Learning Research, vol. 18, no. 1, pp. 1–48, 2017. 20
M. Ott, M. Auli, D. Grangier, and A. Conneau, “Scaling neural ma chine translation,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018, pp. 1–12.
B. Zhang, Q. Liu, S. Wang, and W. Li, “Neural machine translation for low-resource languages: A survey,” ACM Computing Surveys, vol. 53, no. 6, pp. 1–36, 2020.
R. Sennrich, B. Haddow, and A. Birch, “Improving neural machine translation models with monolingual data,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL), 2016, pp. 86–96.
Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, O. Levy, M. Lewis, L. Zettlemoyer, and V. Stoyanov, “Roberta: A robustly optimized bert pretraining approach,” arXiv preprint arXiv:1907.11692, 2019.
N. Mungoli, “Scalable, distributed ai frameworks: leveraging cloud com puting for enhanced deep learning performance and efficiency,” arXiv preprint arXiv: 2304.13738, 2023.
“Enhancing control and responsiveness in chatgpt: A study on prompt engineering and reinforcement learning techniques.
Nayani, A. R., Gupta, A., Selvaraj, P., Singh, R. K., & Vaidya, H. (2019). Search and Recommendation Procedure with the Help of Artificial Intelligence. In International Journal for Research Publication and Seminar (Vol. 10, No. 4, pp. 148-166).
Chaudhary, A. A., Chaudhary, A. A., Arif, S., Calimlim, R. J. F., Rodolfo Jr, F. C., Khan, S. Z., ... & Sadia, A. (2024). The impact of ai-powered educational tools on student engagement and learning outcomes at higher education level. International Journal of Contemporary Issues in Social Sciences, 3(2), 2842-2852.
Gupta, A. (2021). Reducing Bias in Predictive Models Serving Analytics Users: Novel Approaches and their Implications. International Journal on Recent and Innovation Trends in Computing and Communication, 9(11), 23-30.
Singh, R. K., Vaidya, H., Nayani, A. R., Gupta, A., & Selvaraj, P. (2020). Effectiveness and future trend of cloud computing platforms. Journal of Propulsion Technology, 41(3).
Selvaraj, P. (2022). Library Management System Integrating Servlets and Applets Using SQL Library Management System Integrating Servlets and Applets Using SQL database. International Journal on Recent and Innovation Trends in Computing and Communication, 10(4), 82-89.
Gupta, A. B., Selvaraj, P., Kumar, R., Nayani, A. R., & Vaidya, H. (2024). Data processing equipment (UK Design Patent No. 6394221). UK Intellectual Property Office.
Vaidya, H., Selvaraj, P., & Gupta, A. (2024). Advanced applications of machine learning in big data analytics. [Publisher Name]. ISBN: 978-81-980872-4-9.
Selvaraj, P., Singh, R. K., Vaidya, H., Nayani, A. R., & Gupta, A. (2024). AI-driven multi-modal demand forecasting: Combining social media sentiment with economic indicators and market trends. Journal of Informatics Education and Research, 4(3), 1298-1314. ISSN: 1526- 4726.
Selvaraj, P., Singh, R. K., Vaidya, H., Nayani, A. R., & Gupta, A. (2024). AI-driven machine learning techniques and predictive analytics for optimizing retail inventory management systems. European Economic Letters, 13(1), 410-425.
Gupta, A., Selvaraj, P., Singh, R. K., Vaidya, H., & Nayani, A. R. (2024). Implementation of an airline ticket booking system utilizing object-oriented programming and its techniques. International Journal of Intelligent Systems and Applications in Engineering, 12(11S), 694- 705.
Donthireddy, T. K. (2024). Leveraging data analytics and ai for competitive advantage in business applications: a comprehensive review.
DONTHIREDDY, T. K. (2024). Optimizing Go-To-Market Strategies with Advanced Data Analytics and AI Techniques.
Karamchand, G. (2024). The Role of Artificial Intelligence in Enhancing Autonomous Networking Systems. Aitoz Multidisciplinary Review, 3(1), 27-32.
Karamchand, G. (2024). The Road to Quantum Supremacy: Challenges and Opportunities in Computing. Aitoz Multidisciplinary Review, 3(1), 19-26.
Karamchand, G. (2024). The Impact of Cloud Computing on E-Commerce Scalability and Personalization. Aitoz Multidisciplinary Review, 3(1), 13-18.
Karamchand, G. K. (2024). Scaling New Heights: The Role of Cloud Computing in Business Transformation. International Journal of Digital Innovation, 5(1).
Karamchand, G. K. (2023). Exploring the Future of Quantum Computing in Cybersecurity. Journal of Big Data and Smart Systems, 4(1).
Karamchand, G. K. (2023). Automating Cybersecurity with Machine Learning and Predictive Analytics. Journal of Computational Innovation, 3(1).
Karamchand, G. K. (2024). Networking 4.0: The Role of AI and Automation in Next-Gen Connectivity. Journal of Big Data and Smart Systems, 5(1).
Karamchand, G. K. (2024). Mesh Networking for Enhanced Connectivity in Rural and Urban Areas. Journal of Computational Innovation, 4(1).
Karamchand, G. K. (2024). From Local to Global: Advancements in Networking Infrastructure. Journal of Computing and Information Technology, 4(1).
Karamchand, G. K. (2023). Artificial Intelligence: Insights into a Transformative Technology. Journal of Computing and Information Technology, 3(1).
MALHOTRA, P., & GULATI, N. (2023). Scalable Real-Time and Long-Term Archival Architecture for High-Volume Operational Emails in Multi-Site Environments.
Bhikadiya, D., & Bhikadiya, K. (2024). EXPLORING THE DISSOLUTION OF VITAMIN K2 IN SUNFLOWER OIL: INSIGHTS AND APPLICATIONS. International Education and Research Journal (IERJ), 10(6).
Bhikadiya, D., & Bhikadiya, K. (2024). Calcium Regulation And The Medical Advantages Of Vitamin K2. South Eastern European Journal of Public Health, 1568-1579.
Yi, J., Xu, Z., Huang, T., & Yu, P. (2025). Challenges and Innovations in LLM-Powered Fake News Detection: A Synthesis of Approaches and Future Directions. arXiv preprint arXiv:2502.00339.
Huang, T., Yi, J., Yu, P., & Xu, X. (2025). Unmasking Digital Falsehoods: A Comparative Analysis of LLM-Based Misinformation Detection Strategies. arXiv preprint arXiv:2503.00724.
Wang, Y., & Yang, X. (2025). Research on Edge Computing and Cloud Collaborative Resource Scheduling Optimization Based on Deep Reinforcement Learning. arXiv preprint arXiv:2502.18773.
Wang, Y., & Yang, X. (2025). Research on Enhancing Cloud Computing Network Security using Artificial Intelligence Algorithms. arXiv preprint arXiv:2502.17801.
Huang, T., Xu, Z., Yu, P., Yi, J., & Xu, X. (2025). A Hybrid Transformer Model for Fake News Detection: Leveraging Bayesian Optimization and Bidirectional Recurrent Unit. arXiv preprint arXiv:2502.09097.
Nayani, A. R., Gupta, A., Selvaraj, P., Singh, R. K., & Vaidya, H. (2019). Search and Recommendation Procedure with the Help of Artificial Intelligence. In International Journal for Research Publication and Seminar (Vol. 10, No. 4, pp. 148-166).
Gupta, A. (2021). Reducing Bias in Predictive Models Serving Analytics Users: Novel Approaches and their Implications. International Journal on Recent and Innovation Trends in Computing and Communication, 9(11), 23-30.
Singh, R. K., Vaidya, H., Nayani, A. R., Gupta, A., & Selvaraj, P. (2020). Effectiveness and future trend of cloud computing platforms. Journal of Propulsion Technology, 41(3).
Selvaraj, P. (2022). Library Management System Integrating Servlets and Applets Using SQL Library Management System Integrating Servlets and Applets Using SQL database. International Journal on Recent and Innovation Trends in Computing and Communication, 10(4), 82-89.
Gupta, A. B., Selvaraj, P., Kumar, R., Nayani, A. R., & Vaidya, H. (2024). Data processing equipment (UK Design Patent No. 6394221). UK Intellectual Property Office.
Vaidya, H., Selvaraj, P., & Gupta, A. (2024). Advanced applications of machine learning in big data analytics. [Publisher Name]. ISBN: 978-81-980872-4-9.
Selvaraj, P., Singh, R. K., Vaidya, H., Nayani, A. R., & Gupta, A. (2024). AI-driven multi-modal demand forecasting: Combining social media sentiment with economic indicators and market trends. Journal of Informatics Education and Research, 4(3), 1298-1314. ISSN: 1526-4726.
Selvaraj, P., Singh, R. K., Vaidya, H., Nayani, A. R., & Gupta, A. (2024). AI-driven machine learning techniques and predictive analytics for optimizing retail inventory management systems. European Economic Letters, 13(1), 410-425.
Gupta, A., Selvaraj, P., Singh, R. K., Vaidya, H., & Nayani, A. R. (2024). Implementation of an airline ticket booking system utilizing object-oriented programming and its techniques. International Journal of Intelligent Systems and Applications in Engineering, 12(11S), 694-705.
Nayani, A. R., Gupta, A., Selvaraj, P., Kumar, R., & Vaidya, H. (2024). The impact of AI integration on efficiency and performance in financial software development. International Journal of Intelligent Systems and Applications in Engineering, 12(22S), 185-193.
Vaidya, H., Nayani, A. R., Gupta, A., Selvaraj, P., & Singh, R. K. (2023). Using OOP concepts for the development of a web-based online bookstore system with a real-time database. International Journal for Research Publication and Seminar, 14(5), 253-274.
Selvaraj, P., Singh, R. K., Vaidya, H., Nayani, A. R., & Gupta, A. (2023). Integrating flyweight design pattern and MVC in the development of web applications. International Journal of Communication Networks and Information Security, 15(1), 245-249.
Selvaraj, P., Singh, R. K., Vaidya, H., Nayani, A. R., & Gupta, A. (2014). Development of student result management system using Java as backend. International Journal of Communication Networks and Information Security, 16(1), 1109-1121.
Nayani, A. R., Gupta, A., Selvaraj, P., Singh, R. K., & Vaidya, H. (2024). Online bank management system in Eclipse IDE: A comprehensive technical study. European Economic Letters, 13(3), 2095-2113.
Rele, M., & Patil, D. (2023). Revolutionizing Liver Disease Diagnosis: AI-Powered Detection and Diagnosis. International Journal of Science and Research (IJSR), 12, 401-7.
Rele, M., & Patil, D. (2023, September). Machine Learning based Brain Tumor Detection using Transfer Learning. In 2023 International Conference on Artificial Intelligence Science and Applications in Industry and Society (CAISAIS) (pp. 1-6). IEEE.
Rele, M., & Patil, D. (2023, July). Multimodal Healthcare Using Artificial Intelligence. In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.
