대한전자공학회:학술대회논문집 (Proceedings of the IEEK Conference)
- 대한전자공학회 2004년도 학술대회지
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- Pages.768-771
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- 2004
Automated Classification of Audio Genre using Sequential Forward Selection Method
- Lee Jong Hak (Dept of Information and Computer Science, Dankook University) ;
- Yoon Won lung (Dept of Information and Computer Science, Dankook University) ;
- Lee Kang Kyu (Dept of Information and Computer Science, Dankook University) ;
- Park Kyu Sik (Dept of Information and Computer Science, Dankook University)
- 발행 : 2004.08.01
초록
In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital signal processing approach. From the 20 second query audio file, 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS (Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we verify the superior performance of the SFS method that provides near
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