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DOI:http://dx.doi.org/10.26855/jamc.2020.12.001

An Improved Method of Raga Content Assessment in Songs with Therapeutic Benefits

Swarima Tewari, Soubhik Chakraborty*

Department of Mathematics, Birla Institute of Technology, Mesra, Ranchi-835215, India.

*Corresponding author: Soubhik Chakraborty

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Date: October 14,2020 Hits: 179, How to cite this paper

Abstract

A raga, in Indian classical music, be it Hindustani or Carnatic, is a melodic struc-ture with fixed notes and a set of rules that characterize a particular mood con-veyed by performance. Ragas have well acknowledged rich emotional content (the so called raga rasa) but a common man generally lacks the aesthetic sense to understand these ragas and hence cannot derive their therapeutic benefits completely. Accordingly when it comes to music medicine and music therapy, a nice idea would be to first render songs based on a particular raga one by one with gradually increasing raga content in them and then render this specific raga itself whereby determining the raga content in a song becomes an interesting and intriguing research problem. In an earlier work, we proposed a technique relying on correlation coefficient (based on pitch that characterize a musical note) of melodic shapes, as a measure of melodic similarity, to address the issue. Considering the limitations of correlation coefficient, in the present work, we propose an improved method by incorporating more features into our analysis. These additional features include note duration, inter onset interval and pitch movements between the notes. The experimental results are encouraging.

References

[1] Datta, A. K., Solanki, S. S., Sengupta, R., Chakraborty, S., Mahto, K., and Patranabis, A. (2017). Signal Analysis of Hindustani Classical Music, Springer.

[2] Chakraborty, S., Ranganayakulu, R., Chauhan, S., Solanki, S. S., and Mahto, K. (2009). A Statistical Analysis of Raga AhirBhairav. Journal of Music and Meaning, Vol. 8, sec. 4, http://www.musicandmeaning.net/issues/showArticle.php?artID=8.4.

[3] Jairazbhoy, N. A. (1995). The Ragas of North Indian Music: Their Structure & Evolution. Bombay: Popular Praka-shan.

[4] Chakraborty, S., Krishnapryia, K., Loveleen, Chauhan, S., Solanki, S. S., and Mahto, K. (2010). Melody Revisited: Tips from Indian Music Theory. International Journal of Computational Cognition, Vol. 8(3), 26-32.

[5] Chakraborty, S., Mazzola, G., Tewari, S., and Patra, M. (2014). Computational Musicology in Hindustani Music. Springer.

[6] Adiloglu, K., Noll, T., and Obermayer, K. A. (2006). Paradigmatic Approach to Extract the Melodic Structure of a Musical Piece. Journal of New Music Research, Vol. 35(3), 221-236.

[7] Dutta, D. (2006). Sangeet Tattwa, Pratham Khanda (in Bengali), BratiPrakashani, 5th ed.

[8] Singh, S. B., Chakraborty, S., Jha, K. M., Chandra, S., Prakash, S., and Tewari, S. (2016). Music and Medicine: Healing Brain Injury Through Ragas. CBH publications.

[9] S. Tewari and S. Chakraborty. (2020). Modeling a Raga-Based Song and Evaluating its Raga Content: Why it Mat-ters in a Clinical Setting, S. K. Sahana and V. Bhattacharjee (eds.), Advances in Computational Intelligence, Ad-vances in Intelligent Systems and Computing 988, https: //doi.org/10.1007/978-981-13-8222-2_21, pp. 255-264, Springer Nature Singapore Pte Ltd. 

[10] Tewari, S. and Chakraborty, S. (2011). A Statistical Analysis of Raga Bhairavi. Acoustic Waves, S. K. Srivastava, Kailash, K. Chaturvedi (Ed.), Shree Publishers and Distributors, New Delhi, pp. 329-336.

[11] Priyadarshini, P. and Chakraborty, S. (2017). Using Statistical Modeling, Rate of Change of Pitch and Inter Onset Interval to Distinguish Between Restful and Restless Ragas. Communications in Mathematics and Statistics, Vo-lume 5(2), pp. 199-212.

[12] Beran, J. and Mazzola, G. (1999). Analyzing musical structure and performance- a statistical approach. Statistical Science, Vol. 14 (1), 47-79.

[13] Pearce, M. T., Wiggins, G. A. (2004). Improved Methods for Statistical Modelling of Monophonic Music. Journal of New Music Research. Vol. 33, Article 4, pp. 367-385.

[14] Wiggins, G. A., Pearce, M. T., and Müllensiefen, D. (2011). Computational Modeling of Music Cognition and Musical Creativity. The Oxford Handbook of Computer Music edited by R. T. Dean, Oxford University Press.

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An Improved Method of Raga Content Assessment in Songs with Therapeutic Benefits
How to cite this paper: Swarima Tewari, Soubhik Chakraborty. (2020) An Improved Method of Raga Content Assessment in Songs with Therapeutic Benefits. Journal of Applied Mathematics and Computation, 4(4), 113-117.
DOI: http://dx.doi.org/10.26855/jamc.2020.12.001

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