Computational Musicology in Hindustani Music [Paperback]

The book opens with a short introduction to Indian music, in particular classical Hindustani music, followed by a chapter on the role of statistics in computational musicology. The authors then show how to analyze musical structure using Rubato, the music software package for statistical analysis, in particular addressing modeling, melodic similarity and lengths, and entropy analysis; they then show how to analyze musical performance. Finally, they explain how the concept of seminatural composition can help a music composer to obtain the opening line of a raga-based song using Monte Carlo simulation.

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The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.

An Introduction to Hindustani Music.- The Role of Statistics in Computational Musicology.- Introduction to Rubato: The Music Software for Statistical Analysis.- Modeling the Structure of Raga Bhimpalashree: A Statistical Approach.- Analysis of Lengths and Similarity of Melodies in Raga Bhimpalashree.- Raga Analysis Using Entropy.- Modeling Musical Performance Data with Statistics.- A Statistical Comparison of Bhairav (A Morning Raga) and Bihag (A Night Raga).- Seminatural Composition.- Concluding Remarks.

This book makes a huge contribution in providing an accessible account published by a mainstream and highly reputed publisher of the complex mathematical foundation of a historical and established musical tradition that has not been considered by many Western musicologists. (Sara Kalvala, Computing Reviews, February, 2016)

Dr. Soubhik Chakraborty earned his Ph.D. in statistics and he is currently an Associate Professor in the Dept. of Applied Mathematics at the Birla Institute of Technology. His research interests include algorithm analysis and music analysis. He plays the harmonium. Prof. Dr. Guerino Mazzola earned his Ph.D. in Mathematics from Zurich University. He wrote the groundbreakil3d