文章基本信息

标题：Classification of Audio Data using Support Vector Machine
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作者：Shruti Aggarwal ; Naveen Aggarwal
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2011
卷号：2
期号：3(Version 2)
出版社：Ayushmaan Technologies
摘要：Audio mining is to extract audio signals for indicating patterns and features of audio data to get data mining results. Various audio features like Mel frequency Cepstral Coefficient (MFCC), Linear Predictive Coefficient (LPC), Compactness, Spectral Flux (SF), Band Periodicity (BP), Zero Crossing Rate (ZCR) etc are used to classify audio data into various classes. Various classification algorithms such as Naive Bayes, FT, J48, ID3 and LibSVM are used to classify audio data into defined classes. Using various performance parameters such as True Positive (TP) Rate, False Positive (FP) Rate etc., results of various classification algorithms are compared.
关键词：Audio Mining; audio classification; classification algorithms;Support Vector Machine; LibSVMO