Segmentation of Lecture Videos Based on Spontaneous Speech Recognition

In the past decade, the number of digital academic lecture videos has increased dramatically as recording technology has become more affordable. There are technical problems in the use of recorded lectures for learning: the problem of easy access to the multimedia lecture video content and the problem of finding the appropriate information. The first step to a solution is to segment the videos into smaller cohesive areas. In this paper, we present a study on segmenting recorded lecture videos based on their transcripts with standard linear text segmentation algorithm (LTSA). Our evaluation dataset is based on different languages and various speakers´ recordings. Three different tests analyze the outcome of ten algorithms: 1) Whether LTSA is able to segment the transcript into the slide transitions. 2) The presentation slides are used as an additional resource for the segmenting procedure. 3) Analyzing the topic boundaries independently from the slide transitions.