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More About This Title Music Navigation with Symbols and Layers: Toward Content Browsing with IEEE 1599 XML Encoding
English
Anyone wanting to realize a computer application using IEEE 1599 -- music and computer science departments, computer generated music research laboratories (e.g. CCRMA at Stanford, CNMAT at Berkeley, and IRCAM in Paris), music library conservationists, music industry frontrunners (Apple, TDK, Yamaha, Sony), etc. -- will need this first book-length explanation of the new standard as a reference.
The book will include a manual teaching how to encode music with IEEE 1599 as an appendix, plus a CD-R with a video demonstrating the applications described in the text and actual sample applications that the user can load onto his or her PC and experiment with.
English
DENIS L. BAGGI was a faculty member at the University of Applied Sciences (SUPSI) near Lugano in Southern Switzerland and the director of the Laboratory for Semantic Systems and Multimedia. He was the chairman of the IEEE-SA Working Group in charge of Standard IEEE 1599 to encode and represent music, and is presently the CEO of Think-Lab.ch, a Swiss company dedicated to innovation.
GOFFREDO M. HAUS is the Director of the Department of Computer Science and Dean of the Department of Information and Communication Technology at the University of Milan. He has published nearly 100 scientific papers, dozens of other kinds of publications, and several books and CD-ROMs concerning computer applications in music.
Both Baggi and Haus cofounded the IEEE Computer Society Task Force on Computer Generated Music.
English
A Brief Introduction to the IEEE 1599 Standard xv
Denis L. Baggi and Goffredo M. Haus
List of Contributors xvii
1 THE IEEE 1599 STANDARD 1
Denis L. Baggi and Goffredo M. Haus
1.1 Introduction 1
Important Features of IEEE 1599 2
Examples of Applications of IEEE 1599 to Increase Music Enjoyment 3
Example I: A Score with Different Versions: “King Porter Stomp,” by Jelly Roll Morton 6
Example II: A Jazz Piece with No Score: “Crazy Rhythm” 6
Example III: An Opera Using the Composer’s Manuscript: Tosca, by Giacomo Puccini 9
Example IV: “Peaches en Regalia,” by Frank Zappa 9
Example V: “Il mio ben quando verrà,” by Giovanni Paisiello 12
Example VI: Brandenburg Concerto No. 3, by J.S. Bach 14
Example VII: Blues, a Didactical Tool to Learn Jazz Improvisation 14
Example VIII: “La caccia,” from Antonio Vivaldi’s Four Seasons (“Autumn”) 16
Example IX: A Musicological Fantasy: Tauhid, a Piece of Free Jazz 17
Conclusions 19
Acknowledgments 19
References 19
2 ENCODING MUSIC INFORMATION 21
Luca A. Ludovico
2.1 Introduction 21
2.2 Heterogeneous Descriptions of Music 22
2.3 Available File Formats 23
2.4 Key Features of IEEE 1599 24
2.5 Multi-Layer Structure 25
2.6 The Logic Layer 27
2.7 The Spine 29
2.7.1 Inter-layer and Intra-layer Synchronization 31
2.7.2 Virtual Timing and Position of Events 32
2.7.3 How to Build the Spine 33
References 36
3 STRUCTURING MUSIC INFORMATION 37
Adriano Baratè and Goffredo M. Haus
3.1 Introduction 37
3.2 Music Objects and Music Algorithms 38
3.2.1 Music Objects 38
3.2.2 Music Algorithms 38
3.2.3 Music Objects and Music Algorithms in IEEE 1599 39
3.3 Petri Nets 39
3.3.1 Petri Nets Extension: Hierarchy 40
3.3.2 Petri Nets Extension: Probabilistic Arc Weights 43
3.4 Music Petri Nets 44
3.4.1 Music Petri Nets in IEEE 1599 47
3.5 Music Analysis Using Music Petri Nets 47
3.6 Real-Time Interaction with Music Petri Nets 50
3.7 Conclusions 55
References 55
4 MODELING AND SEARCHING MUSIC COLLECTIONS 57
Alberto Pinto
4.1 Introduction 57
4.2 Describing Music Content 58
4.2.1 Music Search Engines 59
4.3 Music Description in IEEE 1599 60
4.3.1 Chord Grid Objects 64
4.3.2 Petri Net Objects 65
4.3.3 Analysis Objects 65
4.3.4 MIR Objects 66
4.4 The Theoretical Framework 66
4.4.1 The Model Perspective 66
4.4.2 Categories 67
4.5 Music Modeling and Retrieval in IEEE 1599 67
4.5.1 MIR Model 68
4.5.2 MIR Object 69
4.5.3 MIR Subobject 70
4.5.4 MIR Morphisms 70
4.5.5 MIR Features 70
4.5.6 GraphXML Encoding 71
4.6 Case Study: Graph-Categorial Modeling 72
4.6.1 Content Description 72
4.6.2 Content Retrieval 72
4.6.3 MIR Model 73
4.6.4 MIR Object and Subobject 74
4.6.5 MIR Morphism 75
References 75
5 FEATURE EXTRACTION AND SYNCHRONIZATION AMONG LAYERS 77
Antonello D’Aguanno, Goffredo M. Haus, and Davide A. Mauro
5.1 Introduction 77
5.2 Encoding Synchronization Information 78
5.2.1 Extraction of Synchronization Data 82
5.2.2 Case Study 84
5.3 Overview of Synchronization Algorithms 84
5.4 VarSi: An Automatic Score-to-Audio Synchronization Algorithm Based on the IEEE 1599 Format 88
5.4.1 Score Analysis 89
5.4.2 Audio Analysis 90
5.4.3 Decisional Phase 91
References 94
6 IEEE 1599 AND SOUND SYNTHESIS 97
Luca A. Ludovico
6.1 Introduction 97
6.2 From Music Symbols to Sound Synthesis 98
6.2.1 Translating Symbols into a Performance Language 99
6.2.2 Interpretative Models 105
6.2.3 Audio Rendering and Synchronization 106
6.3 From Sound Synthesis to Music Symbols 108
6.4 An Example of Encoding 110
6.5 Conclusions 113
References 114
7 IEEE 1599 APPLICATIONS FOR ENTERTAINMENT AND EDUCATION 115
Adriano Baratè and Luca A. Ludovico
7.1 Introduction 115
7.2 IEEE 1599 for Entertainment 116
7.3 IEEE 1599 for Music Education 117
7.4 IEEE 1599-Based Music Viewers 118
7.5 Case Studies 120
7.5.1 Navigating and Interacting with Music Notation and Audio 120
7.5.2 Musicological Analysis 121
7.5.3 Instrumental and Ear Training 126
7.5.4 IEEE 1599 Beyond Music 132
References 132
8 PAST PROJECTS USING SYMBOLS FOR MUSIC 133
Denis L. Baggi
8.1 Brief History 133
8.2 Bass Computerized Harmonization (BA-C-H) 134
8.3 Harmony Machine 135
8.4 NeurSwing, an Automatic Jazz Rhythm Section Built with Neural Nets 141
8.5 The Paul Glass System 145
8.6 A Program That Finds Notes and Type of a Chord and Plays It 147
8.7 Summary of Projects 149
8.8 Conclusions 150
References 150
Appendix A. Brief History of IEEE 1599 Standard, and Acknowledgments 151
Appendix B. IEEE Document-Type Defi nitions (DTDs) 153
Appendix C. IEEE 1599 Demonstration Videos 177
Index 179
