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Audio Content Classification by Using Spectral Features
Qian Xueming 1,Liu Guizhong 1 *,Wang Huan 2,Li Zhi 1,Nan Nan 1,Wang Zhe 1,Sun Li 1
1.School of Electronics and Information Engineering, Xi’an Jiaotong University
2.
*Correspondence author
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Funding: 教育部博士点基金等(No.200050698033)
Opened online:10 February 2009
Accepted by: none
Citation: Qian Xueming ,Liu Guizhong,Wang Huan .Audio Content Classification by Using Spectral Features[OL]. [10 February 2009] http://en.paper.edu.cn/en_releasepaper/content/28696
 
 
Audio information play important role in speaker identification and semantic based video content analysis, indexing and retrieval. Sometimes, audio clues are dominant in determining the story unit types. In this paper, a new temporal spectral feature including the proposed spectral histogram is integrated for audio content classification. By analysis the temporal spectral distribution, we adaptively determine the effective feature vectors for audio content discrimination. Finally, several one class support vector machine (SVM) are used to classify each audio clip into following five types: silence, pure music, pure speech, speech with noise background (Speech+Noise), and speech with music background (Speech+Music). Experimental results show the effectiveness of the proposed methods.
Keywords:Audio classification;SVM;zero-cross rate;bandwidth;spectral histogram
 
 
 

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