An Effective Method on Content Based Music Feature Extraction
Based on the theories of frequency domain and time domain signal processing,wavelet analysis,and singular value decomposition (SVD),an effective method for content based music feature extraction is proposed in this paper.Music feature can be divided into three parts by this method,which are frequency feature,auditory perceptual feature,and statistical characteristic of beat.The characteristic of each music can be well described by these features.The results of logistic regression classification model and linear support vector machine (SVM) classification model which is on a data set consists of several different styles of music and use the feature extraction method in this paper show the high precision of 95.33% in average,and also prove the effectiveness of the proposed method.Feature extraction is the foundation of content based recommendation,retrieval,classification,and cluster.Hence this method has good prospect in these area.
music audio analysis wavelet analysis SVD music feature extraction
Zhanchun Gao Yuting Liu Yanjun Jiang
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China
国际会议
重庆
英文
780-784
2015-12-19（万方平台首次上网日期，不代表论文的发表时间）