DocumentCode
3434834
Title
Speech music discrimination using class-specific features
Author
Beierholm, Thomas ; Baggenstoss, Paul M.
Author_Institution
GN ReSound A/S, Taastrup, Denmark
Volume
2
fYear
2004
fDate
23-26 Aug. 2004
Firstpage
379
Abstract
In this paper the application of the class-specific features approach to classification is demonstrated for the problem of discriminating between speech and music. Feature extraction is class-specific and can therefore be tailored to each class meaning that segment size, model orders and the type of features used can be different for the classes. The performance of the discriminator is evaluated and an example of how classification is possible without training is given.
Keywords
audio signal processing; feature extraction; music; speech processing; audio signal processing; class specific feature; feature extraction; speech music discrimination; Auditory system; Data mining; Density functional theory; Feature extraction; Information analysis; Instruments; Multiple signal classification; Pattern classification; Speech enhancement; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-2128-2
Type
conf
DOI
10.1109/ICPR.2004.1334226
Filename
1334226
Link To Document