The week's pick
Reseach Article
Data Mining Techniques for Automatic Recognition of Carnatic Raga Swaram Notes
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 52 - Number 10 |
| Year of Publication: 2012 |
| Authors: K Priya, R. Geetha Ramani, Shomona Gracia Jacob |
10.5120/8236-1444
|
K Priya, R. Geetha Ramani, Shomona Gracia Jacob . Data Mining Techniques for Automatic Recognition of Carnatic Raga Swaram Notes. International Journal of Computer Applications. 52, 10 ( August 2012), 4-9. DOI=10.5120/8236-1444
Abstract
Data Mining is a powerful technology nowadays to discover and analyze large data sets. It has its applications in various fields of Arts, Science and Engineering. One such field is Music. Music is a form of arts which comes under fine arts category. It may be melody or rhythmic. It is broadly categorized as western music and classical music. Carnatic music is a form of south Indian classical music which comprises of swarams (7 notes) to evolve music. This research work deals with automatic identification of Carnatic raga Swaram notes through Data Mining algorithms. The training sets considered for the work are Avarohanam notes of 72 melakartha raga and 212 Janya raga. C4. 5 decision tree algorithm, Random Tree and Rule Induction algorithm were utilized to classify the Melakartha raga and the Janya raga. However the Janya raga swaram notes were also investigated through the use of appropriate feature relevance algorithms namely Feature ranking, Correlation based Feature Selection (CFS) filtering, and Fast Correlation based Filter (FCBF) filtering. The Melakartha raga data set was accurately classified with 100% accuracy by all the aforementioned classification techniques while predictor attributes selected through feature ranking algorithm produced nearly 90% accurate classification with Rule Induction algorithm on the Janya raga data.
References
- Data Mining Concepts, http://www. thearling. com/ text/dmwhite/dmwhite. htm
- Principles in Data mining, http://en. wikipedia. org/wiki/
- Data mining Technologies, http://www. anderson. ucla. edu /faculty/jason. frand/teacher/technologies/
- Ries, R. E. (1969). The Cultural Setting of South Indian Music. Asian Music (University of Texas Press) 1 (2): 22–31. doi: 10. 2307/833909
- Gaurav Pandey, et al. , Tansen: A system for automatic Raga identification, IICAI, 2003
- Priya K and Dr. Geetha Ramani R, 2012, GA method of evolving Carnatic Music Concert Swaras in the proceeding of ICCA 2012, ACM.
- Xi Shao, C. Xu, and M. S. Kankanhalli, Unsupervised classification of music genre using hidden markov model, in Proc. of the IEEE International Conf. of Multimedia Expo, 2004.
- Roberto Basili, Alfredo Serafini, Armando Stellato, Classification of Musical Genre: A Machine Learning Approach, @c 2004 Universitat Pompeu Fabra.
- Noris Mohd Norowi, Shyamala Doraisamy, Rahmita Wirza, Factors affecting Genre Classification: An investigation incorporating non-western musical forms, 2005 Queen Mary, University of London, pp. 13-20
- B. Tarakeswara Rao1, Sivakoteswararao Chinnam2, P Lakshmi Kanth3, M. Gargi4, Automatic Melakartha Raaga Identification System: Carnatic Music, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 1, No. 4, 2011, pp. 43-48
- Rajeswari Sridhar1, and T. V. Geetha, Raga Identification of Carnatic music for Music information retrieval, International journal on recent trends in Engineering, vol. 1,2009
- Rajeswari Sridhar and T. V. Geetha, Comparison of signal separation algorithms as applied to Carnatic music, FRSM 2007
- Rajeswari Sridhar and T. V. Geetha, Swara identification of Carnatic music, IEEE Computer Society press, proceeding of ICIT 2006.
- Gopala Krishna Koduri, Sankalp Gulati, Preeti Rao, A Survey of Raaga Recognition Techniques and Improvements to the State-of-the-Art, Proceedings of Sound and Music Computing, 2011. Italy.
- Surendra Shetty and K. K. Achary, Raga Mining of Indian Music by Extracting Arohana-Avarohana Pattern, International Journal of Recent Trends in Engineering Vol. 1, No. 1, May 2009,pp. 362-366
- Shreyas Belle and Preethi Rao, 2009, Raga Identification by using Swara Intotation, Journal of ITC sangeet research academy, vol 23, 2009.
- Sudha. R and Karthiravel A,2009,A system tool for identifying ragas using MIDI files in proceedings of ICCEE2009, IEEE Explore, Dubai, 644-647,DOI: 10. 1109/ICCEE. 2009. 49
- Krishna A S and Raj Kumar PV, 2011, Identification of carnatic ragas using hidden markov models in proceedings of IEEE Explore, Smolience, 107-110, DOI: 10. 1109/SAMI. 2011. 5738857
- Tanagra Tutorials and Software, www. tanagraltd. com
- Mrs. Shomona Gracia Jacob and Dr. R. Geetha Ramani. Article: Discovery of Knowledge Patterns in Clinical Data through Data Mining Algorithms: Multi-class Categorization of Breast Tissue Data. International Journal of Computer Applications 32(7):46-53, October 2011. Published by Foundation of Computer Science, New York, USA.
- I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations
- S. G. Jacob, R. Geetha Ramani, Evolving Efficient Classification Rules from Cardiotocography data through data mining methods and techniques, European Journal of Scientific Research, Vol. 78, Issue 3, pp. 468-470.
- S. G. Jacob, R. Geetha Ramani, Mining of Classification Patterns in Clinical Data through Data Mining Algorithms, ICACCI '12, August 03 - 05 2012, CHENNAI, India. Copyright 2012 ACM 978-1-4503-1196pp. 997-1003
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