This thesis will describe a system for the production of generative music through specific methodology, and provide an approach for the delivery of this material. The system and body of work will be targeted specifically at the personal listening audience. As the largest current consumer of music in all genres of music, this represents the largest and most applicable market to develop such a system for. By considering how recorded media compares to concert performance, it is possible to ascertain which attributes of performance may be translated to a generative media. In addition, an outline of how fixed media has changed how people listen to music directly will be considered. By looking at these concepts an attempt is made to create a system which satisfies societies need for music which is not only commodified and easily approached, but also closes the qualitative gap between a static delivery medium and concert based output. This is approached within the context of contemporary classical music. Furthermore, by considering the development and fragmentation of the personal listening audience through technological developments, a methodology for the delivery of generative media to a range of devices will be investigated. A body of musical work will be created which attempts to realise these goals in a qualitative fashion. These works will span the development of the composition methodology, and the algorithmic methods covered. A conclusion based on the possibilities of each system with regard to its qualitative output will form the basis for evaluation. As this investigation is seated within the field of music, the musical output and composition methodology will be considered as the primary deciding factor of a system's feasibility. The contribution of this research to the field will be a methodology for the composition and production of algorithmic music in realtime, and a feasible method for the delivery of this music to a wide audience.

A system for generative rhythmic modeling is presented. The work aims to explore computational models of creativity, realizing them in a system designed for realtime generation of semi-improvisational music. This is envisioned as an attempt to develop musical intelligence in the context of structured improvisation, and by doing so to enable and encourage new forms of musical control and performance; the systems described in this work, already capable of realtime creation, have been designed with the explicit intention of embedding them in a variety of performance-based systems. A model of qaida, a solo tabla form, is presented, along with the results of an online survey comparing it to a professional tabla player's recording on dimensions of musicality, creativity, and novelty. The qaida model generates a bank of rhythmic variations by reordering subphrases. Selections from this bank are sequenced using a feature-based approach. An experimental extension into modeling layer- and loop-based forms of electronic music is presented, in which the initial modeling approach is generalized. Starting from a seed track, the layer-based model utilizes audio analysis techniques such as blind source separation and onset-based segmentation to generate layers which are shuffled and recombined to generate novel music in a manner analogous to the qaida model.

This is a study of the way in which digital audio and a number of key associated technologies that rely on it as a framework have changed the creation, production and dissemination of music, as witnessed by my own creative practice. The study is built on my own work as an electronic musician and composer and draws from numerous collaborations with not only other musicians but also researchers and artists, as documented through commissions, performances, academic papers and commercial releases over an 9 year period from 2007 to 2016. I begin by contextualising my own musical practice and outlining some prominent themes associated with the democratisation of computing that the work of this thesis interrogates as a critical framework for the production of musical works. I go on to assess how works using various techniques afforded by digital audio may be interpreted as progressively instantiating a digital ontology of music. In the context of this digital ontology of music I propose a method of analysis and criticism of works explicitly concerned with audio analysis and algorithmic processes based on my interpretation of the concept of `hypertext', wherein the ability for computers to analyse, index and create multi-dimensional, non-linear links between segments of digital audio is best described as hypertextual. In light of this, I contextualise the merits of this reading of music created using these affordances of digital audio through a reading of several key works of 20th century music from a hypertextual perspective, emphasising the role information theory and semiotics have to play in analyses of these works. I proffer this as the beginnings of a useful model for musical composition in the domain of digital audio which I seek to explore through my own practice. I then describe and analyse, both individually and in parallel numerous works I have undertaken that seek to interrogate the intricacies of what it means to work in the domain of digital audio with audio analysis, machine listening, algorithmic and generative computational processes and consider the ways in which aspects of this work might be seen as contributing useful and novel insights into music creation by harnessing properties intrinsic to digital audio as a medium. Finally, I emphasise, based on the music and research presented in the thesis, the extent to which digital audio and the harnessing of increasingly complex computational systems for the production and dissemination of music has changed the ontology of music production, a situation which I interpret as creating both substantial challenges, but also great possibilities for the future of music.

iGrooving is a generative music mobile application specifically designed for runners. The application’s foundation is a step-counter that is programmed using the iPhone’s built-in accelerometer. The runner’s steps generate the tempo of the performance by mapping each step to trigger a kick-drum sound file. Additionally, different sound files are triggered at specific step counts to generate the musical performance, allowing the runner a level of compositional autonomy. The sonic elements are chosen to promote a meditative aspect of running. iGrooving is conceived as a biofeedback-stimulated musical instrument and an environment for creating generative music processes with everyday technologies, inspiring us to rethink our everyday notions of musical performance as a shared experience. Isolation, dynamic changes, and music generation are detailed to show how iGrooving facilitates novel methods for music composition, performance and audience participation.

Generative music creates indeterminate systems from which music can emerge. It provides a particularly instructive field for problems of ontology, semiotics, aesthetics, and ethics addressed in poststructuralist literary theory. I outline how repetition is the ultimate basis of musical intelligibility and of memory in general. The extension of these abstractions beyond tonal music to sound in general is afforded by the concrete iterability of audio recording media. Generative systems delineate a music that is repeatable in principle and in certain qualities, though not in specific forms; a music that produces emergent complexities from novel combinations, retaining the potential to surprise. I study how noise is prevailingly presented as complementary to intention, and how music that complicates intention entails discourses of noise and purity. I compare competing narratives for the role of noise in the development of Western music under classical, avant-garde, and experimental traditions. Music functions across these narratives as a proxy for negotiation of individual and collective values, how order is imposed. Expression affirms the metaphysics of presence by averring the socially unmediated interiority of the subject. Experimentalists are skeptical toward expression, yet frequently insist on the asemiotic self-sufficiency of music. Generative musicians extend this animism, imputing living intelligence behind sounds. I further examine discourses surrounding creation and interpretation in the arts and human sciences, in particular how listening is a manner of composition. Poiesthesis is a play of materials as well as signs, facilitated by recording in a recombinant practice distinct from the encodings of notation and the approximate repetitions of aural tradition. Generative music deals in entities that are neither composition nor instrument, and yet both. The music market and the aesthetic field alike struggle to control the valuation of desubstantiated texts of generative systems, producing a kind of agoraphobia. As play is decentered from authorial intent, so must critical evaluation be. I critique the pervasive yet tacit Western notion that human technoculture plays out on a continuum from Africa to robotics, ciphers for bodily essence and intellectual autism. This cultural projection turns out to resonate throughout the history of Western music’s regard of self and other.

Hur låter miljöförstöring – Självgenererande och slumpmässig sprungen ur statistiska data är ett mastersarbete som fokuserar på hur man kan omvandla data till att kontrollera musik och ljud. Om vi tillåter konstnärliga uttryck, med data som utgångspunkt, kan det få oss att uppleva och förstår original data på ett nytt sätt? Projektets resultat består av sju generativa kompositioner, där parametrar är kontrollerade av olika typer av miljödata, och försöker utforska forskningsområdet sonifikation och generativ musik genom att ställa frågan: Hur låter miljöförstöring? Med generativ musik menas att musiken skapar, utvecklar och förändrar sig själv utifrån de verktyg som bildats inom detta projekt. Texten går också djupare in på metoden av att utveckla dessa verktyg för att möjliggöra liknande kompositioner i framtiden. Med erfarenheter av att använda slumpmässiga parametrar för att manipulera bakgrundsdetaljer, utforskar det här projekt istället möjligheten att utveckla de metoderna och applicera det på hela kompositioner. De sju kompositionerna ligger också till grund för utforskandet av området sonifikation. I tidigare forskning har ämnet främst bemöts ifrån ett vetenskapligt perspektiv. Syftet med det här projektet har istället varit att bemöta det inom ramarna för musikalisk gestaltning och ett konstnärligt perspektiv. Begreppet sonifikation betyder, användandet av icke-talande ljud som uppmärksammar data och statistik, med målet att agera som ett substitut, eller ett komplement, till att visualisera data. Utifrån dessa kompositioner reflekterar sedan texten kring generativ musik i allmänhet, och sonifikation i synnerhet, där bland annat möjligheterna, framtida forskning och autenticiteten inom sonifikation tas upp. / What does environmental pollution sound like? – Self generative and randomized music interprets data is a master thesis focused on transforming data and letting it control music and sounds. If we create artistic outputs out of data, will it allow us to experience and understand the original data in a new way? The core, and the result, of this project where seven compositions, created and controlled by different environmental data which tries to explore the research areas of sonification and generative music by asking the question: What does environmental pollution sound like? Generative music means that the music creates, develops and changes itself based on the established tools that this project provides. This thesis also focuses on the method of developing these tools in order to enable similar productions in the future. With previous experiences in using randomized events, to manipulate details in a production, this project delves deeper into applying the same technique to a whole composition. The seven compositions were formed in order to understand and reflect upon the research areas of sonification. Earlier research tends to approach the subject from a scientific perspective. The purpose of this project was to instead approach it from a more artistic perspective. Sonification means, the use of non-speech audio to perceptualize data which enables the possibilities as an alternative, or complement, to visualize the original data. Drawing from these seven compositions, this thesis also discusses generative music and sonification in general, as well as the opportunities, future research and authenticity of sonification. / <p>Bifogad ljudfil är ett kollage av de sju kompositionerna som arbetet resulterat i, med anledning av att i framtiden kunna publiceras i sin helhet.</p>

Theory as an approach to generative composition and interactive computer music. Inspired by the notion of Performance Indeterminacy, software has been developed that attempts to simulate the interactions of improvising performers using a multi-agent system based on the ‘Iterated Prisoner’s Dilemma’. Composition activities and programming activities have formed a symbiotic relationship throughout the creation of the portfolio as each has constantly informed the other. Stylistically, the works presented fall into the experimental genre, although individually they address a wide range of aesthetic goals. The main contribution of this portfolio is a new approach to generative composition based on behavioural models, creating a sense of form bottom-up through modelling the social dynamics of music performance. Through this approach, the direct modelling of musical structures is avoided; instead larger scale forms emerge through the interactions of an ensemble of ‘improvising’ agents. This method offers a departure from previous complex systems work in the area of music, creating computer models of specific musical situations. Links between the Iterated Prisoner’s Dilemma and music are also established and combined with current music technologies. / Thesis(Ph.D.)- University of Adelaide, Elder Conservatorium of Music, 2008

Theory as an approach to generative composition and interactive computer music. Inspired by the notion of Performance Indeterminacy, software has been developed that attempts to simulate the interactions of improvising performers using a multi-agent system based on the ‘Iterated Prisoner’s Dilemma’. Composition activities and programming activities have formed a symbiotic relationship throughout the creation of the portfolio as each has constantly informed the other. Stylistically, the works presented fall into the experimental genre, although individually they address a wide range of aesthetic goals. The main contribution of this portfolio is a new approach to generative composition based on behavioural models, creating a sense of form bottom-up through modelling the social dynamics of music performance. Through this approach, the direct modelling of musical structures is avoided; instead larger scale forms emerge through the interactions of an ensemble of ‘improvising’ agents. This method offers a departure from previous complex systems work in the area of music, creating computer models of specific musical situations. Links between the Iterated Prisoner’s Dilemma and music are also established and combined with current music technologies. / Thesis(Ph.D.)- University of Adelaide, Elder Conservatorium of Music, 2008

Une mise en contexte présente l’évolution de la prise de décision du créateur dans des environnements où la technologie est sans cesse plus impliquée et autonome. Un survol des techniques génératives, de ses origines en musique jusqu’aux arts numériques, est présenté. Trois œuvres réalisées dans le cadre de ce projet de recherche-création sont ensuite analysées. Les outils et les techniques utilisés pour la réalisation de ces projets à dominante générative sont expliqués et commentés. Verklärter Rohr fait l’objet d’une analyse plus poussée sur l’aspect comprovisationnel de mon travail. Le développement de mon langage audiovisuel tel qu’il se rapporte au concept de synchrèse sera aussi examiné. L’analyse de Machine In The Shell, sert de terrain d’investigation pour expliciter des stratégies de spatialisation et de techniques d’écriture. L’analyse de Gu(I)t(A)rs développe sur l’utilisation de diverses technologies dont le Leap Motion, la synthèse par modélisation physique et l’intelligence artificielle. / Questions related to the evolution of creative decision-making are discussed, in relation to technology that is becoming more and more involved. An overview of generative techniques, from its origins in music to contemporary digital arts, is then presented. Then, three works produced as part of this research-creation project are analyzed. The different tools and techniques I used in making these works are explained and commented. Verklärter Rohr is the subject of a more in-depth analysis. The comprovisational angle of my work, as well as the development of my audiovisual language as it relates to the concept of synchresis will be discussed. An analysis of Machine In The Shell explain the strategies of spatialization and writing techniques I used. The analysis of Gu(I)t(A)rs expands on the use of various technologies including Leap Motion, physical modeling synthesis and artificial intelligence.

The Well Trained Algorithm is a composition that challenges prevailing conceptions of the use of AI tools in music through the reconceptualising of JukeBox, a generative AI model for music, as an instrument in its own right. Here, I am coining the term ‘instrumentisation’ to describe a methodology for applying the qualities and associations of a musical instrument to a traditionally non-musical object. To showcase this conceptual approach, this model of thinking is applied to aid in the composition of the AI-generated musical piece, The Well Trained Algorithm. Through this process of ‘instrumentisation’, musical terms such as tuning and timbre are redefined to better relate to the specific affordances of an artificially intelligent system. The composition is informed, then, by an exploration of a system's instrumental possibilities, leading to a more effective and artistic use of the technology in the creative process. The seminal works of J. S. Bach and La Monte Young, The Well Tempered Clavier and The Well Tuned Piano, respectively, provide a historical, musical, and theoretical context for the piece as well as the datasets used to fine-tune the JukeBox model. With this thesis, I ask if, through a process of ‘instrumentisation’ AI technology can be successfully reconceptualised as a musical instrument as a means to promote artistic expression.