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《Computer Engineering》 2011-07
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Environmental Sound Classification Based on Manifold Learning and SVM

LI Yong,LI Ying,YU Qing-qing(College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108,China)  
In order to take full advantage of the information contained in the eco-environmental sounds,this paper presents a ecological environmental sounds classification technology based on manifold learning algorithm and Support Vector Machine(SVM).Select four different kinds of audio characteristics those are dynamics,timbre,pitch and rhythm and then calculate the feature vectors corresponding to those four audio characteristics.So as to reduce the complexity of data processing,it makes use of an improved Laplacian feature mapping for dimensionality reduction.To improve the accuracy,the SVM classifier is used to classify the dimension-reduced feature vectors because SVM have advantages in dealing with the data that is of few samples,nonlinear and high dimension.Experimental results show that the technology can be used to classify ecological environmental sounds quickly and accurately.
【Fund】: 国家自然科学基金资助项目(61075022);; 福建省教育厅A类科技基金资助项目(JA09021)
【CateGory Index】: TN912.3
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