• DocumentCode
    2804736
  • Title

    Using Artistic Markers and Speaker Identification for Narrative-Theme Navigation of Seinfeld Episodes

  • Author

    Friedland, Gerald ; Gottlieb, Luke ; Janin, Adam

  • Author_Institution
    Int. Comput. Sci. Inst., Berkeley, CA, USA
  • fYear
    2009
  • fDate
    14-16 Dec. 2009
  • Firstpage
    511
  • Lastpage
    516
  • Abstract
    This article describes a system to navigate Seinfeld episodes based on acoustic event detection and speaker identification of the audio track and subsequent inference of narrative themes based on genre-specific production rules. The system distinguishes laughter, music, and other noise as well as speech segments. Speech segments are then identified against pre-trained speaker models. Given this segmentation and the artistic production rules that underlie the "situation comedy" genre and Seinfeld in particular, the system enables a user to browse an episode by scene, punchline, and dialog segments. The themes can be filtered by the main actors, e.g. the user can choose to see only punchlines by Jerry and Kramer. Based on the length of the laughter, the top-5 punchlines are identified and presented to the user. The segmentation is then presented in an Applet-based graphical video browser that is intended to extend a typical YouTube videoplayer.
  • Keywords
    multimedia computing; speaker recognition; Applet-based graphical video browser; Seinfeld episodes; YouTube videoplayer; acoustic event detection; artistic markers; genre-specific production rules; narrative-theme navigation; speaker identification; speech segments; Cable TV; Event detection; Layout; Loudspeakers; NIST; Navigation; Production systems; Speech; Streaming media; Video on demand; browser; narrative themes; speaker identification; video navigation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia, 2009. ISM '09. 11th IEEE International Symposium on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4244-5231-6
  • Electronic_ISBN
    978-0-7695-3890-7
  • Type

    conf

  • DOI
    10.1109/ISM.2009.20
  • Filename
    5362650