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The interest of today’s generation to learn from video lectures is becoming popular due to its considerable advantages and easy availability than classroom learning. To involve into this, many institutes and organizations are using this method for teaching and learning. An enormous amount of data is generated in video lecturing form. To extract the desired information from the desired video from this vast video information available on internet becomes difficult. In this paper, we have used techniques for automatically retrieving the information from video files to collect it as a metadata for those files. For efficient retrieval of text from videos we use the OCR (Optical Character Recognition) tool to extract text from slides and ASR (Automatic Speech Recognition) tool for recognizing information from speech given by the speaker. First, we do segmentation and classification of video frames for identifying the key frames. Then the OCR and ASR tool is used for extracting the information from video slides and audio speech respectively. The collected data can be stored as a metadata for the file. Finally, the search can be made more efficient by applying clustering and ontology concept.
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Duc Phuong Nguyen, Martin Guggisberg, Helmar Appendix: Springer-Author Discount Burkhart,: Multimedia Information and Mobile-Learning, Eighth IEEE International Symposium on Multimedia (ISM’06), 2006.
Haojin Yang and Christoph Meinel,: Content Based Lecture Video Retrieval Using Speech and Video Text Information, IEEE Transactions On Learning Technologies, vol. 7, no. 2, April–June 2014.
P.P. Chakraborty, Programming and Data Structure (Video), C Programming-I, Indian Institute of Technology, Kharagpur. Available at http://nptel.ac.in/course.php?disciplineId=106.
Madhav Gitte, Harshal Bawaskar, Sourabh Sethi, Ajinkya Shinde,: Content based video retrieval system, International Journal of Research in Engineering and Technology, volume: 03 issue: 06 | June 2014.
E. Leeuwis, M. Federico, and M. Cettolo,: Language modelling and transcription of the ted corpus lectures, in Proc. IEEE Int. Conf. Acoust., Speech Signal Process., 2003, pp. 232–235.
Wolfgang Hürst, Thorsten Kreuzer, Marc Wiesenhütter, A qualitative study towards using large vocabulary automatic speech recognition to index recorded presentations for search and access over the web:, ICWI, page 135–143, IADIS, 2002.
Xiaoqiang Xiao, Jasha Droppo and Alex Acero,: Information retrieval methods for automatic speech recognition, IEEE international conference on Acoustic Speech and Signal Processing, 2010.
Matthew Cooper,: Presentation Video Retrieval using Automatically Recovered Slide and Spoken Text, Multimedia content and mobile devices, SPIE proceedings, vol. 8667, 2013.
Alexander G. Hauptmann, Rong Jin, and Tobun D. Ng,: Video Retrieval using Speech and Image Information, Electronic Imaging Conference (EI’03), Storage Retrieval for Multimedia Databases, Santa Clara, CA, January 20–24, 2003.
Tiecheng Liu and John R. Kender,: Rule-based semantic summarization of instructional videos, IEEE International conference on Image Processing, vol 1, 2002.
Chirag Patel, Atul Patel, Dharmendra Patel, Optical Character Recognition by Open Source OCR Tool Tesseract: A Case Study, International Journal of Computer Applications (0975–8887) volume 55, no. 10, October 2012.
Vijaya Kumar Kamabathula, Sridhar Iyer, Automated Tagging To Enable Fine-Grained Browsing of Lecture Videos, IEEE International Conference on Technology for Education (T4E), 2011.
Harald Sack, Jörg Waitelonis,: Integrating Social Tagging and Document Annotation for Content-Based Search in Multimedia Data, Proceedings of the 1st Semantic Authoring and Annotation Workshop (SAAW’06), Athens (GA), USA, (November 2006 ) ISSN 1613-0073.
Dong Yu, Li Deng,: Automatic Speech Recognition, Springer Signal and communication technology, 2012.
Hong Liu, and Xiaohong Yu,: Application Research of k-means Clustering Algorithm in Image Retrieval System, Proceedings of the Second Symposium International Computer Science and Computational Technology, 2009.
- Retrieving Instructional Video Content from Speech and Text Information
Ashwini Y. Kothawade
Dipak R. Patil
- Springer Singapore