Authors :
Navya D; Nimitha V R
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/sv2ejwuf
Scribd :
https://tinyurl.com/2v3hk5er
DOI :
https://doi.org/10.5281/zenodo.14558069
Abstract :
Language barriers remain a challenge in our
connected world. This project aims to develop an offline
translation tool for seamless communication without
internet access. Using localized language data, pre-
trained machine learning models, and natural language
processing, the app offers bidirectional translation of
common phrases in multiple languages. Lightweight and
user-friendly, it embeds translation algorithms directly
onto devices, ensuring privacy and security. Ideal for
travel, education, emergencies, and fostering inclusion,
this tool promotes reliable communication and global
connectivity.
Keywords :
Translation, Offline, App, Technology.
References :
- Zhao, L., & Wang, X. (2024). A Preliminary Study on Exploring the Use of Translation Apps and Their Impact on English Learning Strategies. Proceedings of the 2024 IEEE 4th International Conference on Electronic Communications, Internet of Things, and Big Data. IEEE.
- Piwowar, H. (2024). The State of AI in Literary Translation. Journal of Literary Translation Studies.J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73.
- Wang, L., & Zhao, C. (2024). The Impact of Artificial Intelligence on Language Translation: A Review. Journal of Machine Translation and AI Research.
- Tuite, T. (2024). Translation Companies Accelerating Adoption of Large Language Models. Journal of Translation Technologies.
- Hu, J., & Li, Y. (2023). The Impact of Translation Apps on Translation Students’ Performance. Journal of Educational Technology and Translation Studies, 15(3), 234-245.
- Shubha, R. S., & Krithika, S. M. (2023). Survey and Analysis on Language Translator Using Neural Machine Translation. Journal of Computational Linguistics, 31(2), 150-161.
- SDL Trados. (2023). Translation Technology Insights 2023. Inbox Translation and Institute of Translation and Interpreting (ITI) Survey Report.
- Yeger-Lotem, S. D. T., McKinley, M. D., & Xue, N. (2022). Survey of Low-Resource Machine Translation. Machine Translation Research Review, 29(4), 58-71.
- Zhao, L., & Wang, X. (2023). The Impact of Translation Apps on Translation Students' Performance. Journal of Translation Education, 14(1), 103-112.
Language barriers remain a challenge in our
connected world. This project aims to develop an offline
translation tool for seamless communication without
internet access. Using localized language data, pre-
trained machine learning models, and natural language
processing, the app offers bidirectional translation of
common phrases in multiple languages. Lightweight and
user-friendly, it embeds translation algorithms directly
onto devices, ensuring privacy and security. Ideal for
travel, education, emergencies, and fostering inclusion,
this tool promotes reliable communication and global
connectivity.
Keywords :
Translation, Offline, App, Technology.