Music genre classification by analyzing the subband spectrogram

Author

Chih-Hsun Chou ; Bo-Jun Liao

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Chung-Hua Univ., Hsinchu, Taiwan

Volume

3

fYear

2014

fDate

26-28 April 2014

Firstpage

1677

Lastpage

1680

Abstract

In this study, music genre classification based on the characteristics of spectrogram was studied. In the proposed method, the capability of multi-resolution analysis of the wavelet package decomposition (WPD) as well as the dimension reduction ability of the singular value decomposition (SVD) was integrated to extract the desired features. Experimental results with the well-known ISMIR 2004 and GTZAN database were used to verify the performance of the proposed method.

Keywords

music; signal classification; singular value decomposition; wavelet transforms; GTZAN database; ISMIR 2004 database; SVD; WPD; multiresolution analysis; music genre classification; singular value decomposition; spectrogram characteristics; subband spectrogram; wavelet package decomposition; Databases; Feature extraction; Metals; Rocks; Spectrogram; Time-frequency analysis; Training; music genre classification; singular value decomposition; spectrogram; wavelet packet decomposition;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on

Conference_Location

Sapporo

Print_ISBN

978-1-4799-3196-5

Type

conf

DOI

10.1109/InfoSEEE.2014.6946207

Filename

6946207