Case Study
AI Transcription System
A system that converts audio and video lectures into text using Whisper, helping students access searchable learning content.
Problem
Students often struggle to revisit spoken lecture content efficiently, especially when lessons are long or difficult to follow in real time.
Solution
I built a transcription platform that processes uploaded lecture media and converts it into readable text, making it easier for students to review and study.
How It Works
Step 1
Users upload an audio or video lecture.
Step 2
The backend processes the file and sends it through Whisper for transcription.
Step 3
The generated text is stored and displayed in the frontend.
Step 4
Users can review the transcript for learning and revision.
Challenges
Handling media uploads efficiently across the frontend and backend.
Integrating AI transcription into a user-friendly workflow.
Structuring transcripts for practical readability.
Outcome / Impact
The system demonstrates how AI can solve a real educational problem by improving access to spoken academic content.