A NOVEL FRAMEWORK FOR MUSIC STYLE CLASSIFICATION BY USING NAIVE BAYESIAN NETWORK

摘要：

Music style classification becomes more and more application in commercial audience-recommendation. But any simple and efficient method has not been found for solving the great deal of music online. In this paper we developed a framework based on Naive Bayesian Network (NBN) to perform music style classification. We acquired such important features after deeply studying, and construct our specific NBN for music style classification. The results of the experiments in our method indicated that the simplicity and accuracy of music style classification improved greatly.

关键词： Naive Bayesian Network Music Style classification Gaussian BNs

作者: JIAN LUO YAN-MEI LI XIAN-BO HE MING-DONG LI GANG-YUAN ZHANG

作者单位: School of Computer Science China West Normal University Nanchong Sichuan, China

会议类型: 国际会议

会议名称: 3rd International Conference on Mechanical and Electrical Technology(ICMET2011) (2011第三届机械与电气技术国际会议)

会议地点: 大连

会议语种:英文

页码: 113-117

在线出版日期: 2011-08-26（万方平台首次上网日期，不代表论文的发表时间）