Title :
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
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;
Conference_Titel :
Information Science, Electronics and Electrical Engineering (ISEEE), 2014 International Conference on
Conference_Location :
Sapporo
Print_ISBN :
978-1-4799-3196-5
DOI :
10.1109/InfoSEEE.2014.6946207