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
Link To Document :
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