Browsing within Lecture Videos Based on the Chain Index of Speech Transcription

The number of digital lecture video recordings has increased dramatically since recording technology became easier to use. The accessibility and ability to search within this large archive are limited and difficult. Additionally, detailed browsing in videos is not supported due to the lack of an explicit annotation. Manual annotation and segmentation is time-consuming and therefore useless. A promising approach is based on using the audio layer of a lecture recording to obtain information about the lecture's contents. In this paper we're going to present an indexing method for computer science courses based on their existing recorded videos. The transcriptions from a speech-recognition engine (SRE) are sufficient to create a chain index for detailed browsing inside a lecture video. The index structure and the evaluation of the supplied keywords are presented. The user interface for dynamic browsing of the e-learning contents concludes this paper.