GlobalLearn: An Efficient Multilingual Textual Summary for Education Videos

Educational videos have become a preferred medium for learning, offering advantages such as self-paced study, the ability to revisit concepts, and a distraction-free environment. However, the effective- ness of such videos can be amplified through concise, multilingual textual summaries. This paper introduces GlobalLearn, an AI powered educational video to text summarization application that integrates speech recognition, optical character recognition, and NLP-driven large language models(LLMs) to extract and summarize key concepts from educational videos. By integrating audio and visual transcripts, time-stamped summaries, and multilingual capabilities, GlobalLearn ensures accessibility for diverse global audiences. This user-centric approach not only supports efficient learning and revision, but also bridges linguistic barriers, fostering an inclusive educational ecosystem. The paper explores GlobalLearn’s design and technical architecture, and core functionalities to outline its potential impact on modern education.