Slide Video Lecture Analysis Toolkit

SVLA Toolkit Demo

Making educational videos more accessible and navigable through AI

The SVLA Toolkit uses computer vision, NLP, and machine learning to automatically analyze slide-based lecture videos, creating searchable transcripts, semantic links, and interactive navigation.

✨ Key Features

🎬 Intelligent Analysis: Automated scene detection, OCR text extraction, and speech transcription

🧠 AI-Powered Insights: Semantic links between spoken words and slide content, AI-generated chapters

🎯 Interactive Interface: Click-to-seek navigation, cross-modal highlighting, customizable layout

♿ Accessibility: Reduce visual clutter, focus on content, searchable transcripts

🎮 Demo Experience

Sample Content: Browse pre-processed educational videos including academic lectures, conference presentations, and tutorials.

Interactive Features:

  • Navigate using visual timeline with scene thumbnails
  • Search across both transcript and slide content
  • Experience semantic connections between audio and visual elements
  • Customize interface elements for enhanced accessibility

Try It: Visit the live demo to explore the toolkit's capabilities with sample videos.

🛠 Get Started

Try the Demo: Experience the interface with pre-processed sample videos

Use Your Own Videos: Clone the repository for full functionality including video upload and processing

For Developers: Complete API documentation and technical specifications available on GitHub

🎯 Perfect For

Students: Jump to topics with AI chapters, search visual and spoken content, focus on slides, interact with elements (zoom, moving, customization)

Researchers: Analyze educational video corpora, study multimodal content relationships

Built with FastAPI, OpenCV, Whisper, and Sentence-BERT • MIT License • Contribute on GitHub