Music Information Retrieval (MIR) is a science of retrieving information about music both statically and dynamically. Music Information Retrieval is a high learning curve and is beyond the knowledge of text Information Retrieval (IR). The two main approaches in which MIR is dealt with is meta-data based and content based. The classification of music based on compositions, artists and other static information is called text-based retrieval. The content based MIR actually focuses on musical content retrieval such as pitch, melody, rhythm etc. which can be used for extracting audio features for identification and classification of ragas dynamically.

MIR, ICM, HPS, Pattern recognition

[1] http://onlinecourses.nptel.ac.in
[2] http://en.wikipedia.org/wiki/Glossary_of_Carnatic_music_terms
[3] V. Krishnan, Mathematics of Melakartha Ragas in Carnatic Music, UMass Lowell, August 2012.
[4] R. Shridhar, et al., “Raga Identification of Carnatic music for Music Information Retrieval”, International Journal of Recent Trends in Engineering, Vol. 1(1), pp. 571-574, 2009.
[5] p. Dighe, et al., ”Swara Histogram Based Structural Analysis And identification Of Indian Classical Ragas”,International Society for Music Information Retrieval, 2013.
[6] M. Kamble, "Raga Identification Techniques of Indian Classical Music: An Overview”,Innovation in engineering science and technology (NCIEST-2015), pp. 100 – 105, 2015.
[7] R. Joseph, et al., ”Carnatic Raga Recognition”, Indian Journal of Science and Technology, Vol 10(13), 17485-110326, April 2017.
[8] P. Reddy, et al., “Automatic Raaga Identification System for Carnatic Music Using Hidden Markov Model”, Global Journal of Computer Science and Technology,Vol. 11(22) December 2011.
[9] K. Srimanip, et al., ” A Comparative Study Of Carnatic And Hindustani Raga Systems By Neural Network Approach”, International Journal of Neural Networks,Vol 2(1), pp. 35-38, 2012.
[10] P. Rao et al.,“Audio Metadata Extraction: The Case For Hindustani Classical Music” Department Of Electrical Engineering, Indian Institute Of Technology Bombay, Proc. of SPCOM 2012.
[11] P. Kirthika, et al., “Frequency Based Audio Feature Extraction For Raga Based Musical Information Retrieval Using LPC and LSI”, Journal of Theoretical and Applied Information Technology, Vol. 69(3), Pg. No. 582 – 588, November 2014..
[12] S. Dutta, et al. “Raga Verification In Carnatic Music Using Longest Common Segment Set”, 16th International Society for Music Information Retrieval Conference, 2015, pp. 605 – 611.
[13] P. Rajshri, et al., “Harmonium Raga Recognition”, International Journal of Machine Learning and Computing, Vol. 3(4), pp. 352 – 356, August 2013.
[14] Y.Yorozu,M.Hirano,K.Oka,andY.Tagawa,Electronspectroscopystudiesonmagneto-opticalmediaandplasticsubstrateinterface,” IEEETransl.J.Magn.Japan,vol.2,pp.740–741,August1987[Digests9thAnnualConf.MagneticsJapan,p.301,1982].
[15] S. Shetty, et al, “Clustering of Ragas Based on Jump Sequence for Automatic Raga Identification”, ICIP, CCIS 292, pp. 318–328, 2012.
[16] S. Chakraborty, et al., “An Interesting Application Of Simple Exponential Smoothing In Music Analysis”, International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), Vol.2(4), pp. 37 – 44, August 2013.
[17] J. Serra, et al., “Assessing The Tuning Of Sung Indian Classical Music”, International Society for Music Information Retrieval, © 2011
[18] S. Shetty, et al, “Clustering of Ragas Based on Jump Sequence for Automatic Raga Identification”, ICIP, CCIS 292, pp. 318–328, 2012.
[19] G. K. Kouduri, et al., “A Survey of Raaga Recognition Techniques and Improvements to the State-of-the-Art”, Proc. of sound and Music computing, 2011.
[20] T. Rao, et al., "Some Studies on of Raaga Emotions of Singers Using Gaussian Mixture Model", International Journal for Modern Trends in Science and Technology, Vol. 3(1), pp. 149-153, 2017.
[21] B. Tiple, et al., “Analysis of Features for Mood Detection in North Indian Classical Music - A Literature Review”, International Journal of Research in computer and communication Technology , Vol. 6(6), pp. 181-185, June- 2017.
[22] 52. K. M. S. Prasad et al., "Speech Features Extraction Techniques for Robust Emotional Speech Analysis/Recognition", Indian Journal of Science and Technology, Vol 10(3), pp 10i3 - 110571