COPYRIGHT AND USE OF THIS THESIS This thesis must be used in accordance with the provisions of the Copyright Act 1968. Reproduction of material protected by copyright may be an infringement of copyright and copyright owners may be entitled to take legal action against persons who infringe their copyright. Section 51 (2) of the Copyright Act permits an authorized officer of a university library or archives to provide a copy (by communication or otherwise) of an unpublished thesis kept in the library or archives, to a person who satisfies the authorized officer that he or she requires the reproduction for the purposes of research or study. The Copyright Act grants the creator of a work a number of moral rights, specifically the right of attribution, the right against false attribution and the right of integrity. You may infringe the author’s moral rights if you: - fail to acknowledge the author of this thesis if you quote sections from the work - attribute this thesis to another author - subjec t this thesis to derogatory treatment which may prejudice the author’s reputation For further information contact the University’s Director of Copyright Services sydney.edu.au/copyright Ontology of Music Performance Variation S I O D T E ·M A RE E ·MUT N M S· E EAD John R. Taylor Sydney Conservatorium of Music University of Sydney A thesis submitted in fulfilment of requirements for the degree of PhilosophiæDoctor (PhD) 2014 Declaration I declare that the research presented here is my own original work and has not been submitted to any other institution for the award of a degree. Signed:................................................................................................... Date:...................................................................................................... ii Abstract Performance variation in rhythm determines the extent that humans per- ceive and feel the effect of rhythmic pulsation and music in general. In many cases, these rhythmic variations can be linked to percussive performance. Such percussive performance variations are often absent in current percus- sive rhythmic models. The purpose of this thesis is to present an interactive computer model, called the PD-103, that simulates the micro-variations in human percussive performance. This thesis makes three main contributions to existing knowledge: firstly, by formalising a new method for modelling percussive performance; secondly, by developing a new compositional soft- ware tool called the PD-103 that models human percussive performance, and finally, by creating a portfolio of different musical styles to demonstrate the capabilities of the software. A large database of recorded samples are classified into zones based upon the vibrational characteristics of the in- struments, to model timbral variation in human percussive performance. The degree of timbral variation is governed by principles of biomechanics and human percussive performance. A fuzzy logic algorithm is applied to analyse current and first-order sample selection in order to formulate an ontological description of music performance variation. Asynchrony values were extracted from recorded performances of three different performance skill levels to create \timing fingerprints" which characterise unique fea- tures to each percussionist. The PD-103 uses real performance timing data to determine asynchrony values for each synthesised note. The spectral content of the sample database forms a three-dimensional loudness/timbre space, intersecting instrumental behaviour with music composition. The re- parameterisation of the sample database, following the analysis of loudness, spectral flatness, and spectral centroid, provides an opportunity to explore iii the timbral variations inherent in percussion instruments, to creatively ex- plore dimensions of timbre. The PD-103 was used to create a music portfo- lio exploring different rhythmic possibilities with a focus on meso-periodic rhythms common to parts of West Africa, jazz drumming, and electroacous- tic music. The portfolio also includes new timbral percussive works based on spectral features and demonstrates the central aim of this thesis, which is the creation of a new compositional software tool that integrates human percussive performance and subsequently extends this model to different genres of music. KEYWORDS: music, computer, electronic, composition, micro-timbre, micro- timing, performance model, electroacoustic, spectral, percussion, jazz drums, software. I would like to dedicate this thesis to my father who unexpectedly passed away in October 2012. His support, encouragement, inspiration, and sense of humour will always stay with me. I would like to dedicate the composition portfolio to Auntie Eileen and Uncle Ted, who passed away in 2010 and 2011. Ee bah gum, I finished it Gelborsh! Finally, I would like to dedicate the PD-103 software to my sons Max and Sam, for their friendship, understanding, and for keeping me laughing. v Acknowledgements I would like to acknowledge my friends and family in the U.K., Australia and Spain, particularly my mother, Lesley Taylor, my brother Scott, my partner in crime Terri, and my Grandma June, for their love and support over the past few years. I would like to give a special thanks to my super- visor, Dr Ivan Zavada for his patience, inspiration and friendship, and to my associate supervisor Dr David Kim-Boyle for his support. I would also like to say a special thank you to Dr Jennifer Rowley and Professor Peter Dunbar-Hall for their support and friendship. I would also like to thank the Apple University Consortium, HCSNet, and the George and Margaret Henderson Music Trust for their financial support and development opportunities. Other academic staff I would like to thank for their support, guidance, and friendship are (in alphabetical order): Dr John Bassett, Professor Di- ana Blom, Dr Charles Fairchild, Matt Hitchcock, Professor Keith Howard, Dr David Larkin, Associate Professor Kathryn Marsh, Jacqueline Mees, Dr Helen Mitchell, Mr Daryll Pratt, Professor Anna Reid, Mr Craig Scott, Dr Michael Smetanin, Pierre St Just, Professor Jonathon Stock, Richard Toop, Dr Michael Webb, Gerard Willems. I would also like to thank a number of general staff, past and present, at the Sydney Conservatorium of Music whose friendship and support have been, and are so very much appreciated (in alphabetical order): Justin Ankus, Stephen Backman, Ross Binfield, Rodney Boatright, Steven Burns, Mar- tin Carroll, Marie Chellos, Elaine Chia, Ivy Chu, Timothy Crowe, David Kinney, Christina Goranitis, Henrietta Holden, Gloria Holland, Andrew vi Humphries, Hideki Isoda, Ting Lee, Julian and Alistair Lockyer, Cynthia Marin, Jan Marshall, Guy McEwan, Siobhain O'Leary, Ahiegwu (Heggy) Odeh, Anthea Parker, Gemifa Parra, Cedric Poon, Katherine Rowell, Adri- enne Sach, Scott Saunders, Peter and Caro Thomas, Rene Tsiknas, Mar- ianne Uy, Stephen Yates, Jos´eand the team of attendants, the cleaning team, the security team, and Dy and all staff in the Jazz Caf´e,for keeping me well fed and appropriately wired on caffeine! Last but not least, I would like to give a special \shout out" to Adam Wil- son, Jarrad Salmon, James Vuong, Dominic Blake, Benadict Carey, Aaron Harding, Rob Cornish, Ross Cooper, the Yates family, the Schaafsma family, Eduardo Suavo, Charlie and Kath Cooper, David Edwards, Leo MacPher- son, Lucia Harvey, Andrew Robertson and Clemente Yap, John George, Oksana Vanyk, and Ros Hurrell for their support, humour, and friendship. Contents Declaration ii Abstract iii Acknowledgements vi List of Figures xiii List of Tables xvi 1 Introduction 1 1.1 Introduction . 2 1.2 Methodological Overview . 6 1.3 Research Aims . 8 1.4 Outline of this Document . 9 2 Limitations of Existing Percussive Software 13 2.1 Humanizing Systems . 14 2.2 Data-Driven Compositional Systems . 19 2.3 Interactive Systems . 22 2.4 Other Performance Modelling Systems . 26 3 Towards a Percussive Performance Model 32 3.1 Why is Modelling Percussive Timbres so Difficult? . 34 3.1.1 The Vibrational Characteristics of Membranophones . 35 3.1.2 The Vibrational Characteristics of Idiophones . 41 3.1.3 Configuration Characteristics . 46 3.1.3.1 Drum Tuning Uniformity . 46 viii CONTENTS 3.1.3.2 Drum Set Configuration . 49 3.1.4 Simulating Percussion using Sound Synthesis . 49 3.2 Why is Modelling Human Performance on a Jazz Drum Set so Difficult? 55 3.2.1 Drum Rudiments and Development Goals . 56 3.2.2 The Analysis of Human Movement . 59 3.2.3 Controlling Instrumental Interaction . 64 3.2.4 Bodily Coordination . 74 3.3 Compositional Application . 79 3.3.1 Computer-Assisted Composition . 81 3.3.2 Live Improvisation . 85 3.3.3 Complex Rhythms . 87 3.3.4 Composing using Feature-Based Parameters . 99 3.3.5 Electroacoustic Application . 100 3.4 Pulse Code Modulation (PCM) Sampling . 101 3.5 Summary Evaluation . 105 3.5.1 Compositional Summary Evaluation . 111 3.5.2 Implications of the Methodology . 113 4 Research Design and Methodological Approach 116 4.1 The Performance Model Defined . 117 4.2 A Method for Representing Micro-Timbre . 120 4.2.1 The Sample Database . 121 4.2.2 Timbral Feature Extraction . 122 4.2.3 Compositional Feature Extraction . 125 4.3 Data Collection: Micro-Timbre . 126 4.3.1 Protocol and Procedure . 126 4.3.2 Equipment . 126 4.3.3 Data Preparation . 131 4.3.4 Feature Extraction . 131 4.3.5 Analysis . 132 4.3.6 Data Preparation . 132 4.4 A Method for Representing Micro-Timing . 133 4.4.1 Timing \Fingerprints" . 133 ix CONTENTS 4.4.2 Temporal Data Extraction . 134 4.5 Data Collection: Performance and Micro-Timing . 134 4.5.1 Participant Overview . 134 4.5.2 Audio Data Collection . 135 4.5.3 Movement Data Collection . 136 4.5.3.1 Audio Reference Material . 136 4.5.3.2 Protocol and Procedure . 136 4.5.3.3 Equipment . 137 4.5.4 Data Extraction Methods . 137 4.5.4.1 Video Recordings . 139 4.5.4.2 Accelerometer Data . 140 4.6 Preliminary Results . 140 4.6.1 Initial Results of Instrumental Micro-Timbre . 141 4.6.2 Data Reduction and Classification by Strike Location .