Paper Contents
Abstract
This is an AI-based speech-to-text translation system designed for real-time tracking and translation across different languages. The model leverages advanced speech recognition and neural machine translation technologies to process spoken input and produce accurate text output in another language. The system has two main components: a robust Automatic Speech Recognition (ASR) module that transcribes spoken input, and an advanced neural translation model that translates the recognized text into a grammatically correct and properly localized variant of the target language. The primary goal of this system is to create a smooth speech-to-text translation interface, addressing language barriers in real time. This system has applications in various fields, including multilingual communication, education, and broadcasting, where real-time translation fosters greater understanding and collaboration. To ensure robust performance and easy deployment, special measures will be taken to address challenges such as variations in accent, background noise, and colloquial expressions.
Copyright
Copyright © 2025 Ankarla Bhargav Raj. This is an open access article distributed under the Creative Commons Attribution License.
