Audio Classification Based on SVM-UBM

摘要：

Audio classification is an important issue in current audio processing and content analysis researches.In this paper we present a high-accuracy audio classification algorithm based on SVM-UBM using MFCCs as classification features.Firstly MFCCs are extracted in frame level,then a Universal Background Gaussian Mixture Model (UBM) is employed to integrate these sequences of frame-level MFCCs within a clip to form the clip-level feature,finally audio classification is performed using SVM with these clip-level features.Four audio types are considered: speech,music,speech over music and environmental sound.The experimental results show that our classification algorithm performs superior to other SVM-based classification system using traditional clip-level features.

作者: Ruijie Zhang Bicheng Li Tianqiang Peng

作者单位: Zhengzhou Information Science and Technology Institute,1001 Mail Box 835＃,Zhengzhou 450002,P.R.China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）