A study on Raga characterization in Indian classical music in the light of MB and BE distribution. Issue 1 (April 2021)

• Record Type: Journal Article
• Authors: Roy, S; Banerjee, A; Sanyal, S; Ghosh, D; Sengupta, R
• Is Part Of: Journal of physics. Volume 1896:Issue 1(2021)
• Publication Date: 2021-04
• Subjects: Maxwell−Boltzmann distribution -- Bose−Einstein distribution -- Indian classical music -- Raga characterization -- temperature; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1896/1/012007
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Raga characterization in Indian classical music is an important aspect of music learning in this country. But the methods usually followed are mostly qualitative. In this study, we intend to quantify such abstractness using measurable parameters. To study musical information congregation quantifiably, we introduce methods based on well-known concepts used in Statistical Physics, namely Maxwell-Boltzmann (MB) and Bose-Einstein (BE) distribution. In this present study, these distributions have been applied on the chosen acoustic signals to find new parameters (equivalent to 'temperature' in physical systems) which can distinguish between different features of different ragas (containing the same notes) in Indian classical music. Music clips chosen were the 'Alap' part of these three different ragas (Marwa, Puriya, Sohini) sung by a legendary classical music maestro. All of the chosen three ragas are based on the following same note structure: Sa, komal Re, shuddh Ga, tivra Ma, shuddh Dha, shuddh Ni. To apply MB statistics to music, it is assumed that different notes with different occurrence frequencies are at different energy levels, the distribution of which follows the MB distribution pattern. In case of BE statistics, a rank-frequency distribution of the time durations of various notes of different ragas is studied. The resulting analysis gives rise to a number of parameters that help to categorize the individual characteristics of ragas. The methods studied here are novel in the music research field and can prove to be useful in the fields of music and speech as quantifying parameters for style identification.