Jayansh sharma1 and Rituparna Datta2, 1Indian Institute of information Technology Una, India, 2Capgemini Technology, India
In a world where connecting and working with people from different countries is more and more important, the language barriers are often the main reasons why the cross border communication and collaboration is not successful. This research paper is about the use of Generative AI models, most notably the MarianMTModel and T5 Model, that enable to go through the linguistic boundaries and create the multilingual forms. The paper, on the other hand, explores the real-life application of these models in a Python environment through the Hugging Face Transformers Library. The paper goes into detailed code sample to show how these models can be used to brightly transfer textual data from one language to another apart from currently utilized models . The experimental design concerns with the translation of different sample data, this data contains individual attributes like name, age, height, weight, and the medical problems, into a number of target languages. Besides, this study not only shows the technical difficulties of model initialization and translation but also it emphasizes the wider meaning of such technology for developing cross-cultural understanding and making the world communication easier. The results underline Generative AI's potentiality to overcome language obstacles, thus enabling the worldwide cooperation, knowledge spread, and cultural exchange.
Generative AI, Marian MTModel, T5 Model, Natural Language Processing, Hugging Face Transformers, Cross-cultural Communication, Language Barriers, Computational Linguistics, Multilingual Translation.
