Semantic Segmentation of Documentary Video using Music Breaks

Abstract

Many documentary videos use background music to help structure the content and communicate the semantic. In this paper, we investigate semantic segmentation of documentary video using music breaks. We first define video semantic units based on the speech text that a video/audio contains, and then propose a three-step procedure for semantic video segmentation using music breaks. Since the music breaks of a documentary video are of different semantic levels, we also study how different speech/music segment lengths correlate with the semantic level of a music break. Our experimental results show that music breaks can effectively segment a continuous documentary video stream into semantic units with an average F-score of 0.91 and the lengths of combined segments (speech segment plus the music segment that follows) strongly correlate with the semantic levels of music breaks