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Kategorie szczegółowe BISAC

Computational Musicology in Hindustani Music

ISBN-13: 9783319365534 / Angielski / Miękka / 2016 / 107 str.

Soubhik Chakraborty; Guerino Mazzola; Swarima Tewari
Computational Musicology in Hindustani Music Soubhik Chakraborty Guerino Mazzola Swarima Tewari 9783319365534 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Computational Musicology in Hindustani Music

ISBN-13: 9783319365534 / Angielski / Miękka / 2016 / 107 str.

Soubhik Chakraborty; Guerino Mazzola; Swarima Tewari
cena 201,72 zł
(netto: 192,11 VAT:  5%)

Najniższa cena z 30 dni: 192,74 zł
Termin realizacji zamówienia:
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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. The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.

Kategorie:
Sztuka, Muzyka
Kategorie BISAC:
Computers > Computer Science
Music > General
Mathematics > Matematyka stosowana
Wydawca:
Springer
Seria wydawnicza:
Computational Music Science
Język:
Angielski
ISBN-13:
9783319365534
Rok wydania:
2016
Wydanie:
Softcover Repri
Numer serii:
000378634
Ilość stron:
107
Waga:
0.18 kg
Wymiary:
23.39 x 15.6 x 0.64
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

"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)

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.

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 groundbreaking book The Topos of Music in 2002 -- its formal language and models are used by leading researchers in Europe and North America and have become a foundation of music software design. Prof. Mazzola has a joint appointment as professor in the School of Music and in the Interdisciplinary Program in Collaborative Arts at the College of Liberal Arts, University of Minnesota. Swarima Tewari has a B.E. in Electrical Engineering and an M.Tech. in Scientific Computing; she is currently doing her Ph.D. in Computational Musicology in the Dept. of Applied Mathematics at the Birla Institute of Technology. Her research focus is music analysis. Moujhuri Patra has an M.Tech. in Computer Science; she is presently working as an Assistant Professor in the Dept. of Computer Applications at the Netaji Subhash Engineering College, Techno India in Garia, Kolkata, and doing her Ph.D. in the Dept. of Applied Mathematics at the Birla Institute of Technology. Her research focus is music analysis.

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.

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



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