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《Journal of Computer Applications》 2010-03
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Abnormal audio recognition algorithm based on MFCC and short-term energy

Lü Xiao-yun,WANG Hong-xia(School of Information Science and Technology,Southwest Jiaotong University,Chengdu Sichuan 610031,China  
Concerning the high complexity and low rate in abnormal audio recognition,the abnormal audio recognition system based on the Mel-Frequency Cepstrum Coefficients(MFCC)and short-term energy was proposed.This feature vector made the Gaussian Mixture Model(GMM)classifier outperform MFCC and Differential MFCC features in classification.The classifier can achieve an average recognition rate of more than 90%,and small computational complexity.The steps of system implementation were elaborated.The simulation results prove the effectiveness of the proposed algorithm.
【Fund】: 国家自然科学基金资助项目(60702025)
【CateGory Index】: TP277;TN912.34
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【Secondary Citations】
Chinese Journal Full-text Database 5 Hits
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