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Topic Development Based Refinement of Audio-Segmented Television News

  • Alfredo Favenza
  • Mario Cataldi
  • Maria Luisa Sapino
  • Alberto Messina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5039)

Abstract

With the advent of the cable based television model, there is an emerging requirement for random access capabilities, from a variety of media channels, such as smart terminals and Internet. Random access to the information within a newscast program requires appropriate segmentation of the news. We present text analysis based techniques on the transcript of the news, to refine the automatic audio-visual segmentation. We present the effectiveness of applying the text segmentation algorithm CUTS to the news segmentation domain. We propose two extensions to the algorithm, and show their impacts through an initial evaluation.

Keywords

Automatic Speech Recognition Curve Segment Topic Development Text Stream Unit Duration 
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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References

  1. 1.
    Delos network of excellence on digital libraries. Internet Site, http://www.delos.info/
  2. 2.
    Andrews, P.: Semantic topic extraction and segmentation for efficient document visualization. Master’s thesis, School of Computer & Communication Sciences, Swiss Federal Institute of Technology, Lausanne (2004)Google Scholar
  3. 3.
    Venkatesh, S., Phung, D.-Q., Duong, T.-V., Bui, H.H.: Topic transition detection using hierarchical hidden markov and semimarkov models. In: Proc. of ACM Multimedia 2005 (2005)Google Scholar
  4. 4.
    Smeaton, A., Lee, H., O’Connor, N.E.: User evaluation of físchlár-news: An automatic broadcast news delivery system. ACM Transactions on Information Systems 24(2), 145–189 (2006)CrossRefGoogle Scholar
  5. 5.
    Hearst, M.A.: Texttiling: Segmenting text into multi-paragraph subtopic passages. Computational Linguistics 23(1), 33–64 (1997)Google Scholar
  6. 6.
    Hearst, M.A., Plaunt, C.: Subtopic structuring for full-length document access. In: Proc. of SIGIR (1993)Google Scholar
  7. 7.
    Qi, Y., Candan, K.-S.: Cuts: Curvature-based development pattern analysis and segmentation for blogs and other text streams. In: Proc. of Hypertext 2006 (2006)Google Scholar
  8. 8.
    Snoek, C.G., Worring, M.: Multimodal video indexing: A review of the state-of-the-art. In: Proc. Multimedia Tools and Applications, pp. 5–35 (2005)Google Scholar
  9. 9.
    Torgerson, S.: Multidimensional scaling: I. theory and method. Psychometrika 17(4) (1952)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Alfredo Favenza
    • 1
  • Mario Cataldi
    • 1
  • Maria Luisa Sapino
    • 1
  • Alberto Messina
    • 2
  1. 1.Universita’ di TorinoItaly
  2. 2.RAI - Centre for Research and Technological InnovationTorinoItaly

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