Analyzing a Raga based Bollywood song: A statistical approach

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Authors

Lopamudra Dutta¹ , Soubhik Chakraborty¹

1. Birla Institute of Technology, Mesra

Conference / event

2nd Congress on Intelligent Systems—CIS 2021, September 2021 (Virtual)

Poster summary

Indian classical music is a cherished part of our national heritage, and Bollywood music plays a significant role in promoting it among the general public. Since music creates patterns that can be statistically analyzed, there is motivation to perform a statistical analysis on a recording of a particular raga-based Bollywood song Aaoge Jab Tum. This analysis would compare the song's characteristics with those of the corresponding raga, such as studying where the song follows the raga rules and where it deviates. Additionally, the study would investigate whether the song's musical notes follow a Multinomial or Quasi Multinomial distribution, whether the melody length is uniformly distributed over the song's lines, and the rhythm through IOI (inter onset interval) graph, and note duration, among other things. The statistical parameterization approach, along with Andrews's plot, would be used to investigate the variation in melody and rhythm throughout the song at different intervals.

Keywords

Raga, Melody, Rhythm, Andrews plot, Statistical parameterization, Multinomial distribution

Research areas

Arts, Statistics

References

1. Lopamudra Dutta and Soubhik Chakraborty, Analyzing a Raga-Based Bollywood Song: A Statistical Approach, in M. Saraswat et al. (eds), Congress on Intelligent Systems, Lecture Notes on Data Engineering and Communications Technologies 114, Springer Nature Pte Ltd, 2022, 217-230, https://doi.org/10.1007/978-981-16-9416-5_16

Funding

1. This research did not receive any funding (No. Not Applicable)

Supplemental files

1. Manuscript   Download

Additional information

Competing interests

No competing interests were disclosed.

Data availability statement

The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request.

Creative Commons license

Copyright © 2023 Dutta et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.