International Journal Of Imaging

Abstract

Real-Time Language Translation Using Transformer Models in Python

Author: Dommala Mokshagna Reddy, Dodla Laxmi Narsimha Reddy, K.Poojitha,Mr. V. Laxman Kumar

Abstract:

This project explores the implementation of real-time language translation leveraging transformer models in Python. Transformers, a type of deep learning architecture, have revolutionized natural language processing (NLP) by enabling more efficient handling of sequential data. By utilizing pre-trained models such as BERT and GPT, combined with fine-tuning techniques, we aim to achieve high accuracy in translating text across multiple languages in real-time.The system is designed to process input text, apply the transformer model for translation, and output the translated text with minimal latency. We discuss the architecture, data preprocessing methods, and the integration of the translation model within a user-friendly application interface. Performance metrics are evaluated against benchmark datasets, demonstrating the efficacy and responsiveness of the proposed system. This work underscores the potential of transformer- based models in enhancing communication across linguisti