Classifying Topics of Video Lecture Contents Using Speech Recognition Technology

Abstract

We explore a speech-based topic classification approach. We generate the transcript of input video lecture based on speech recognition technology and identify the topic by comparing its term-based vector with topic models. The preliminary experiment result shows that the speech-based topic classification works well, with its performance comparable to one that directly uses manual transcripts. The approach also shows robustness against speech recognition errors up to 40.6%.