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Research of Music Classification Based on MFCC Feature and HMM Model(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2008年04期
Page:
112-114
Research Field:
Publishing date:

Info

Title:
Research of Music Classification Based on MFCC Feature and HMM Model
Author(s):
Zhang Yan1; 2; Tang Zhenmin2; Li Yanping2; Zou Yi2
1.College of Information Jinling Institution of Technology,Nanjing 210006,China;2.College of Computer Science,Nanjing University of Science and Technology,Nanjing 210094,China
Keywords:
M e l frequency cepstrum coe fficients;  mus ic c lassifica tion;  hiddenM arkovm ode l
PACS:
TN912.34
DOI:
-
Abstract:
In th is paper, we use hiddenM arkovM odel based onM e-l frequency cepstrum coe ffic ients to c lassify the mus ic. Classification d iv ides the test sam ples into ca tego ries acco rding to the largest like lihood va lue. W e draw seve ra l samp les o f the sam em us ic frequency, identify the results o f the sam ples us ing the voting m ethod, and thus determ ine the ca tego ry o f the audio to further improve c lassifica tion accuracy. W e m ake a s imu la tion exper iment to compare the perform ance o f four different c lassifica tions in the env ironm en ts o f disturbance and nod istabance. The resu lts show that HMM class ification has m ore advantages on perform ance and is less sens itive to d isturbance

References:

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Last Update: 2013-04-24