Music Genre Identification Using SVM and MFCC Feature Extraction

Septian Yogi Yehezkiel, Y. Suyanto
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引用次数: 1

Abstract

 Indonesia  is a very diverse country because it has a vast territory and is occupied by millions of people from various tribe. Therefore, traditional music in Indonesia is also diverse because each region has its own culture and art.  In this study, the author used the Support Vector Machine(SVM) pattern recognition  to identify the Indonesian traditional music genre. This genre identification system is able to produce an accuracy of 83% using MFCC.Keywords : traditional music identification, Mel Frequency Cepstral Coefficient, Support Vector Machine.
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基于SVM和MFCC特征提取的音乐类型识别
印度尼西亚是一个非常多样化的国家,因为它有广阔的领土,被来自不同部落的数百万人占领。因此,印度尼西亚的传统音乐也是多样化的,因为每个地区都有自己的文化和艺术。在本研究中,作者使用支持向量机(SVM)模式识别来识别印尼的传统音乐流派。该类型识别系统使用MFCC能够产生83%的准确率。关键词:传统音乐识别,梅尔频率倒谱系数,支持向量机。
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