Automatic Curation of Content Tables for Educational Videos

Abstract

Traditional forms of education are increasingly being replaced by online forms of learning. With many degrees being awarded without the requirement of co-location, it becomes necessary to build tools to enhance online learning interfaces. Online educational videos are often long and do not have enough metadata. Viewers trying to learn about a particular topic have to go through the entire video to find suitable content. We present a novel architecture to curate content tables for educational videos. We harvest text and acoustic properties of the videos to form a hierarchical content table (similar to a table of contents available in a textbook). We allow users to browse the video smartly by skipping to a particular portion rather than going through the entire video. We consider other text-based approaches as our baselines. We find that our approach beats the macro F1-score and micro F1-score of baseline by 39.45% and 35.76% respectively. We present our demo as an independent web page where the user can paste the URL of the video to obtain a generated hierarchical table of contents and navigate to the required content. In the spirit of reproducibility, we make our code public at https://goo.gl/Qzku9d and provide a screen cast to be viewed at https://goo.gl/4HSV1v.