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
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