NDLI: Feature Selection for Automatic Classification of Chinese Folk Songs

Content Provider	IEEE Xplore Digital Library
Author	Xu, Jieping Wang, Peng Yan, Li
Copyright Year	2008
Abstract	The researches on feature selection play a very important role in the area of classification. In this paper, we introduce a heuristic wrapper method: Classification Contribution-Ratio Based Selection (CCRS). Using RBF neural network as a classifier, we did our experiments on a data set of 74 features extracted from 517 Chinese folk songs which come from 10 regions. The results show that Root Mean Square, Spectral Flux and Linear Prediction Coefficient are very effective for the classification of 10 kinds of Chinese folk songs. It works better when the number of features is reduced from 74 to 30 and the classification accuracy is improved from 39.74% (using the total 74 features) to 43.208% (using 30 optimal features). At last, we give an illustration of validity of the algorithm, and a comparison with the Fisher Criterion Method which shows the efficiency of CCRS.
Starting Page	441
Ending Page	446
File Size	380324
Page Count	6
File Format	PDF
ISBN	9780769531199
DOI	10.1109/CISP.2008.461
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Costs Data mining Root mean square wrapper method Radial Basis Function neural network classification contribution-ratio Neural networks Signal processing algorithms Pattern classification Production Signal processing Feature extraction Music information retrieval feature selection
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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