Paper Contents
Abstract
The Communication has improved significantly, thanks to the rapid advancements in social media platforms, which have enabled people worldwide to connect, address issues, and find solutions. In today's globalized world, effective communication is crucial, highlighting the importance of language translation. Initially, human translators were used, but this was not a sustainable solution. After extensive research, machine translation technology was introduced, with a novel approach being the Real-Time Language Translator using Reinforcement Learning. Unlike traditional systems that rely on pre-existing parallel texts and supervised learning, a reinforcement learning-based translator improves by interacting with its environment, receiving feedback, and refining its models through rewards for accuracy and penalties for errors. This method leverages deep reinforcement learning to capture contextual and semantic information, enabling more accurate translations. The research focuses on developing this translator for 5-6 languages initially, with plans for future expansion, offering seamless communication across language barriers and making it a valuable tool in fields like international business, diplomacy, and tourism.
Copyright
Copyright © 2024 K.Surya Kiran. This is an open access article distributed under the Creative Commons Attribution License.
