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@article{170544,
        author = {Srikavi.R and Kanmani.M and Prashanti.M},
        title = {Multilingual Language Translator},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {1263-1268},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170544},
        abstract = {The increasing need for effective multilingual communication in the modern world has driven the development of advanced machine-learning-based translation systems. This project introduces a cutting-edge multilingual language translator that leverages transformer architectures like BERT and GPT to provide accurate, real-time translations. By employing state-of-the-art Natural Language Processing (NLP) models, the system ensures context-aware translations that preserve the original meaning and cultural nuances, significantly enhancing cross-lingual communication experiences. To enable seamless interactions in diverse linguistic environments, the translator integrates advanced machine learning algorithms, making it suitable for various applications such as business communication, travel assistance, and educational resources. Its ability to understand context and emotional tone ensures effective and inclusive communication across different cultures. Furthermore, the system supports a wide range of languages, including underrepresented ones, promoting linguistic diversity and cultural preservation. The translator incorporates user feedback mechanisms to continuously refine its accuracy and adaptability, ensuring it meets users' evolving needs. By combining real-time performance with robust language support, this multilingual translator fosters accessibility and inclusivity in global communication.},
        keywords = {Multilingual Translation, NLP, Machine Learning, Context-Aware, Linguistic Diversity.},
        month = {December},
        }