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Performance Comparison of Classification Algorithms in Music Recognition using Violin and Cello Sound Files  

Kim Jae Chun (인하대학교 전자공학과 통신공학연구실)
Kwak Kyung sup (인하대학교 정보통신대학원)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.30, no.5C, 2005 , pp. 305-312 More about this Journal
Abstract
Three classification algorithms are tested using musical instruments. Several classification algorithms are introduced and among them, Bayes rule, NN and k-NN performances evaluated. ZCR, mean, variance and average peak level feature vectors are extracted from instruments sample file and used as data set to classification system. Used musical instruments are Violin, baroque violin and baroque cello. Results of experiment show that the performance of NN algorithm excels other algorithms in musical instruments classification.
Keywords
music; spectral analysis; audio signal; pattern recognition; data mining;
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