Edu Vault: An Interactive, Multilingual, and Intelligent Topic-Conscious Video Discovery System for Enhanced Conceptual Learning Using Advanced NLP Techniques

Lopa Mandal, T. Bhaskara Harsha Vardhan, K. Ganesh Narasimha Reddy, D. Sai Yeswanth Reddy, Sauvik Bal

Abstract


The present work developed an intelligent topic-conscious video discovery system to retrieve videos from YouTube to enhance e-learning. Speech recognition and machine translation techniques have been used to transform educational videos into easy-to-understand, organized content. The platform supports multilingual content and can transcribe, translate, summarize, and illustrate concepts in an effective manner. It also calculates the readability score of the extracted documents to ensure learners’ understanding. The platform uses live data from YouTube, is 93\% accurate, and responds quickly to search queries, in less than a second. The effective management of large data is handled by the four tier Command Query Responsibility Segregation (CQRS) architecture. Using their API simplifies the link up to YouTube and Google translate. This innovative approach provides solutions towards earing language barrier, saves learners time by helping them discover their needs quickly, and simplifies understanding of difficult subjects.

Keywords


Educational videos, NLP, automatic speech recognition, machine translation, transformers, large language models, semantic reasoning, machine learning

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