Verfügbarkeit: Computational Musicology in Hindustani Music

Computational Musicology in Hindustani Music:

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Bibliographische Detailangaben
Beteiligte Personen:	Chakraborty, Soubhik (VerfasserIn), Tewari, Swarima (VerfasserIn), Mazzola, Guerino 1947- (VerfasserIn), Patra, Moujhuri (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	Cham Springer [2014]
Schriftenreihe:	Computational Music Science
Schlagwörter:	Statistik Raga Informationssystem Informatik Musikwissenschaft Rubato > Programm Musikalische Analyse Hindustanimusik Indien Research Hindustani Music Computational Musicology Rubato Statistical Analysis Ragas Seminatural Composition
Links:	http://deposit.dnb.de/cgi-bin/dokserv?id=4756374&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030153900&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Umfang:	XI, 107 Seiten
ISBN:	9783319114712 3319114719

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Datensatz im Suchindex

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adam_text	Contents 1 An Introduction to Indian Classical Music.................................... 1 1.1 A Critical Comparison Between Indian and Western Music . . . 2 1.2 Terminologies Used in Hindustani Classical Music....................... 5 1.2.1 Raga............................................................ 5 1.2.2 Notation Used in Describing Ragas............................... 6 1.3 Systematic Presentation of Ragas....................................... 9 1.4 Remarks............................................................... 12 References................................................................. 13 2 The Role of Statistics in Computational Musicology.......................... 15 2.1 Modeling.............................................................. 17 2.2 Similarity Analysis.................................................. 18 2.3 Rhythm Analysis....................................................... 18 2.4 Entropy Analysis...................................................... 19 2.5 Multivariate Statistical Analysis..................................... 19 2.6 Study of Vamalankars Through Graphical Features of Musical Data................................................................. 20 2.7 The Link Between Raga and Probability................................. 20 2.8 Statistical Pitch Stability Versus Psychological Pitch Stability . . . 21 2.9 Statistical Analysis of Percussion Instruments........................ 22 References................................................................. 23 3 Introduction to RUBATO: The Music Software for Statistical Analysis................................................................... 25 3.1 Architecture.......................................................... 25 3.1.1 The Overall Modularity......................................... 27 3.1.2 Frame and Modules.............................................. 28 3.2 The RUBETTE® Family................................................... 29 3.2.1 MetroRU BETTE®................................................. 30 3.2.2 MeloRUBETTE®................................................... 33 3.2.3 HarmoRUBETTE®.................................................. 35 ix X Contents 3.2.4 PerformanceRUBETTE®....................................... 41 3.2.5 PrimavistaRUBETTE®........................................ 45 References............................................................. 51 4 Modeling the Structure of Raga Bhimpalashree: A Statistical Approach................................................. 53 4.1 Introduction.................................................... 53 4.2 Methodology..................................................... 54 4.2.1 Getting the Musical Data for Structure Analysis........... 55 4.3 Statistical Analysis............................................ 55 4.4 Discussion...................................................... 56 Conclusion............................................................. 58 Appendix............................................................... 59 References............................................................. 60 5 Analysis of Lengths and Similarity of Melodies in Raga Bhimpalashree.......................................................... 61 5.1 Introduction.................................................... 61 5.2 Statistical Analysis of Melody Groups........................... 61 Conclusion............................................................. 64 References....................................................... 64 6 Raga Analysis Using Entropy............................................ 65 6.1 Introduction.................................................... 65 6.1.1 Mean entropy of raga Bhimpalashree........................ 66 6.2 Discussion: Information on a Possible Event E with P(E) = 0. . . 66 Conclusion............................................................. 67 References............................................................. 68 7 Modeling Musical Performance Data with Statistics............... 69 7.1 Statistics and Music............................................ 69 7.2 Time Series Analysis and Music.................................. 70 7.2.1 Time Series Data.......................................... 70 7.2.2 Goal of Time Series Analysis.............................. 70 7.3 Autoregressive Integrated Moving Average........................ 71 7.3.1 Autoregressive Process.................................... 71 7.3.2 Moving Average Process.................................... 71 7.3.3 ARIMA Methodology......................................... 72 7.3.4 Modeling Musical Data..................................... 72 7.3.5 Analysis of Bihag......................................... 73 7.4 Identification of ARIMA (py d, q) Models........................ 73 7.4.1 Autoregressive Components................................. 74 7.4.2 Moving Average Components................................. 74 7.4.3 Mixed Models.............................................. 74 7.5 ACFs and PACFs.................................................. 75 7.6 Estimating Model Parameters..................................... 76 Contents xi 7.7 Model Diagnostics.............................................. 76 7.7.1 Ljung—Box (Q) Statistic for Diagnostic Checking.......... 77 7.8 Modeling: Finding Fitted Model................. 77 7.9 Results and Discussions........................................ 77 7.9.1 Results for Night Raga Bihag............... 78 Conclusion........................................................... 78 References .......................................................... 79 8 A Statistical Comparison of Bhairav (a Morning Raga) and Bihag (a Night Raga)............................................. 81 8.1 IOI Graph...................................................... 83 8.2 Duration Graphs................................................ 84 8.3 RUBATO Analysis................................................ 84 8.4 RUBATO Analysis of Bhairav..................................... 85 8.5 RUBATO Analysis for Raga Bihag................................. 89 Conclusion......................................................... 94 References........................................................... 95 9 Seminatural Composition............................................... 97 9.1 Introduction................................................... 97 9.2 Experimental Results........................................... 99 Conclusion........................................................... 99 Appendix............................................................ 100 References.......................................................... 101 10 Concluding Remarks................................................... 103 References.......................................................... 107
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author	Chakraborty, Soubhik Tewari, Swarima Mazzola, Guerino 1947- Patra, Moujhuri
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spellingShingle	Chakraborty, Soubhik Tewari, Swarima Mazzola, Guerino 1947- Patra, Moujhuri Computational Musicology in Hindustani Music Statistik (DE-588)4056995-0 gnd Raga (DE-588)4176878-4 gnd Informationssystem (DE-588)4072806-7 gnd Informatik (DE-588)4026894-9 gnd Musikwissenschaft (DE-588)4130526-7 gnd Rubato Programm (DE-588)4800454-6 gnd Musikalische Analyse (DE-588)4040814-0 gnd Hindustanimusik (DE-588)4467299-8 gnd
subject_GND	(DE-588)4056995-0 (DE-588)4176878-4 (DE-588)4072806-7 (DE-588)4026894-9 (DE-588)4130526-7 (DE-588)4800454-6 (DE-588)4040814-0 (DE-588)4467299-8 (DE-588)4026722-2
title	Computational Musicology in Hindustani Music
title_auth	Computational Musicology in Hindustani Music
title_exact_search	Computational Musicology in Hindustani Music
title_full	Computational Musicology in Hindustani Music
title_fullStr	Computational Musicology in Hindustani Music
title_full_unstemmed	Computational Musicology in Hindustani Music
title_short	Computational Musicology in Hindustani Music
title_sort	computational musicology in hindustani music
topic	Statistik (DE-588)4056995-0 gnd Raga (DE-588)4176878-4 gnd Informationssystem (DE-588)4072806-7 gnd Informatik (DE-588)4026894-9 gnd Musikwissenschaft (DE-588)4130526-7 gnd Rubato Programm (DE-588)4800454-6 gnd Musikalische Analyse (DE-588)4040814-0 gnd Hindustanimusik (DE-588)4467299-8 gnd
topic_facet	Statistik Raga Informationssystem Informatik Musikwissenschaft Rubato Programm Musikalische Analyse Hindustanimusik Indien
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