Lecture Transcription and Content Summarization using Core Speech Recognition and AI-Agents

I. INTRODUCTION In the era of rapid digital transformation, educational institutions are increasingly adopting technology to en- hance learning experiences. This research presents an AI-driven lecture transcription and summarization sys- tem designed to convert spoken lectures into concise, well- structured PDF summaries, bridging the gap between lengthy lecture content and efficient knowledge retention. The proposed system leverages state-of-the-art speech-to- text models and a multi-layered intelligent agent archi- tecture, encompassing perception, decision-making, and action layers.