Question answering from lecture videos based on an automatic semantic annotation

Abstract

The number of digital lecture video recordings has increased dramatically. The accessibility, usability and the traceability of their content for students-use is limited. Therefore retrieval of audiovisual lecture recordings is a complex task. Speech recognition is applied to create a tentative and deficient transcription of the video recordings. The imperfect transcription is sufficient to generate semantic metadata serialized in an OWL file. A question answering system based on the automatically generated semantic annotations and a semantic search engine are presented. The annotation process is discussed, evaluated and compared to a perfectly annotated OWL file and, further, to a corrected transcript of the lecture.

Faceted search and retrieval based on semantically annotated product family ontology

“…The existing video annotation approaches are based on the analysis of transliteration or transcripts of a video recording [21][22][23], or from the motion detected and extracted from a video recording [24,25]. The later approach is usually ontology-based, where the ontology serves as the knowledge foundation for annotation.…”

“…The later approach is usually ontology-based, where the ontology serves as the knowledge foundation for annotation. Currently, efforts reported in video annotation focus on ontology-assisted manual annotation [26], clip pattern matching and annotation [24,25] and transcript based language processing [22,23].…”