• DocumentCode
    3517769
  • Title

    Automatic TV program genre classification based on audio patterns

  • Author

    Jasinschi, R.S. ; Louie, J.

  • Author_Institution
    Philips Lab., Briarcliff Manor, NY, USA
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    370
  • Lastpage
    375
  • Abstract
    We discuss the automatic classification of TV program genre based on audio patterns. The audio patterns are defined as a set of relative probabilities for a set of mid-level audio categories. First, we describe the extraction of these audio patterns. Second, we discuss how to use these audio patterns for genre classification. Our genre classification differs from current methods used for TV programs in that it does not require the use of an electronic program guide, such as in personal video recorders. Electronic program guides use simple text based information about genre for whole programs. In contrast, we can determine genre information at the level of program segments. This can be important, for example, for TV program rating which allows to deal selectively with program sections. We demonstrate our method on a set of 7 different TV news and talk shows. The experimental results show that the audio patterns for news and talk show that are consistent with the general structure of these programs
  • Keywords
    audio signal processing; pattern recognition; television; TV news shows; TV talk shows; audio pattern extraction; audio patterns; automatic TV program genre classification; mid-level audio categories; program segments; relative probabilities; Business; Data mining; Layout; Motion pictures; Music; Satellite broadcasting; Signal processing; Speech; TV; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Euromicro Conference, 2001. Proceedings. 27th
  • Conference_Location
    Warsaw
  • ISSN
    1089-6503
  • Print_ISBN
    0-7695-1236-4
  • Type

    conf

  • DOI
    10.1109/EURMIC.2001.952477
  • Filename
    952477