Date of Award
Fall 2017
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computing Sciences - (Ph.D.)
Department
Computer Science
First Advisor
Vincent Oria
Second Advisor
James Geller
Third Advisor
Dimitri Theodoratos
Fourth Advisor
Frank Y. Shih
Fifth Advisor
Pierre Gouton
Sixth Advisor
Roger Zimmerman
Abstract
Multimedia is the main source for online learning materials, such as videos, slides and textbooks, and its size is growing with the popularity of online programs offered by Universities and Massive Open Online Courses (MOOCs). The increasing amount of multimedia learning resources available online makes it very challenging to browse through the materials or find where a specific concept of interest is covered. To enable semantic search on the lecture materials, their content must be annotated and indexed. Manual annotation of learning materials such as videos is tedious and cannot be envisioned for the growing quantity of online materials. One of the most commonly used methods for learning video annotation is to index the video, based on the transcript obtained from translating the audio track of the video into text. Existing speech to text translators require extensive training especially for non-native English speakers and are known to have low accuracy.
Recommended Citation
Rajgure, Sheetal, "Annotation of multimedia learning materials for semantic search" (2017). Dissertations. 56.
https://digitalcommons.njit.edu/dissertations/56