Multilingual Video Indexing and Retrieval Employing an Information Extraction Tool for Turkish News Texts: A Case Study

  • Dilek Küçük
  • Adnan Yazıcı
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7022)


In this paper, a multilingual video indexing and retrieval system is proposed which relies on an information extraction tool, a hybrid named entity recognizer, for Turkish to determine the semantic annotations for the considered videos. The system is executed on a set of news videos in English and encompasses several other components including an automatic speech recognition system for English, an English-to-Turkish machine translation system, a news video database, and a semantic video retrieval interface. The performance evaluation demonstrates that the system components achieve promising results which provides evidence for the applicability of the system. The proposed system and its application on the video set are significant as they constitute a plausible case study targeting at the problem of multilingual video indexing and retrieval utilizing information extraction as the central technique for semantic video indexing.


Machine Translation Automatic Speech Recognition News Video Video Retrieval Automatic Speech Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Grefenstette, G., Segond, F.: Multilingual on-line natural language processing. In: Mitkov, R. (ed.) The Oxford Handbook of Computational Linguistics. Oxford University Press, Oxford (2003)Google Scholar
  2. 2.
    Oard, D.W., He, D., Wang, J.: User-assisted query translation for interactive cross-language information retrieval. Information Processing and Management 44(1), 181–211 (2008)CrossRefGoogle Scholar
  3. 3.
    Delezoide, B., Le Borgne, H.: SemanticVox: a multilingual video search engine. In: Proceedings of the ACM International Conference on Image and Video Retrieval (CIVR), pp. 81–84 (2007)Google Scholar
  4. 4.
    Küçük, D., Yazıcı, A.: A hybrid named entity recognizer for Turkish with applications to different text genres. In: Proceedings of the International Symposium on Computer and Information Sciences, pp. 113–116 (2010)Google Scholar
  5. 5.
    Küçük, D., Yazıcı, A.: A text-based fully automated architecture for the semantic annotation and retrieval of Turkish news videos. In: Proceedings of the IEEE International Conference on Fuzzy Systems, pp. 1–8 (2010)Google Scholar
  6. 6.
    Lee, K.F., Reddy, R.: Automatic Speech Recognition: The Development of the Sphinx Recognition System. Kluwer Academic Publishers, Norwell (1988)Google Scholar
  7. 7.
    CMU Sphinx Home Page, (accessed February 21, 2011)
  8. 8.
    Huggins-Daines, D., Kumar, M., Chan, A., Black, A.W., Ravishankar, M., Rudnicky, A.I.: Pocketsphinx: A free, real-time continuous speech recognition system for hand-held devices. In: Proceedings of International Conference on Acoustics, Speech, and Signal Processing, ICASSP (2006)Google Scholar
  9. 9.
    Köprü, S., Yazıcı, A.: Lattice parsing to integrate speech recognition and rule-based machine translation. In: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL), pp. 469–477 (2009)Google Scholar
  10. 10.
    Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: BLEU: A method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL), pp. 311–318 (2002)Google Scholar
  11. 11.
    Küçük, D., Yazıcı, A.: Named entity recognition experiments on Turkish texts. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds.) FQAS 2009. LNCS, vol. 5822, pp. 524–535. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Freitag, D.: Machine learning for information extraction in informal domains. Machine Learning 39(2-3), 169–202 (2000)CrossRefzbMATHGoogle Scholar
  13. 13.
    Küçük, D., Yazıcı, A.: Exploiting information extraction techniques for automatic semantic video indexing with an application to Turkish news videos. Knowledge-Based Systems 24(6), 844–857 (2011)CrossRefGoogle Scholar
  14. 14.
    Youtube, (accessed February 21, 2011)

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Dilek Küçük
    • 1
  • Adnan Yazıcı
    • 2
  1. 1.Power Electronics GroupTÜBİTAK - Uzay InstituteAnkaraTurkey
  2. 2.Department of Computer EngineeringMiddle East Technical UniversityAnkaraTurkey

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