Content-Based Audio Classification Using Support Vector Machines and Independent Component Analysis

Author

Wang, Jia-Ching ; Wang, Jhing-Fa ; Lin, Cai-Bei ; Jian, Kun-Ting ; Kuok, Wai-He

Author_Institution

Dept. of Electr. Eng., National Cheng Rung Univ., Tainan

Volume

4

fYear

0

fDate

0-0 0

Firstpage

157

Lastpage

160

Abstract

In this paper, we present a new audio classification system. First, a frame-based multiclass support vector machine (SVM) for audio classification is proposed. The accuracy rate has significant improvements over conventional file-based SVM audio classifier. In feature selection, this study transforms the log powers of the critical-band filters based on independent component analysis (ICA). This new audio feature is combined with mel-frequency cepstral coefficients (MFCCs) and five perceptual features to form an audio feature set. The superiority of the proposed system has been demonstrated via a 15-class sound database with a 91.7% accuracy rate

Keywords

audio signal processing; independent component analysis; signal classification; support vector machines; audio feature selection; content audio classification; critical-band filter; frame multiclass support vector machine; independent component analysis; mel-frequency cepstral coefficient; sound database; Brightness; Cepstral analysis; Content based retrieval; Discrete cosine transforms; Filters; Independent component analysis; Marine animals; Music information retrieval; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.407

Filename

1699805