VIVO: a Wakeful Instrument

for Collective Musical Embodiment

Fabio Paolizzo

A thesis submitted to the University of Kent in fulfilment of

the degree of Doctor of Philosophy in Music and Technology

3

Abstract 6

Hypothesis 7

Introduction 7

Methodology 9

CHAPTER 1: A GENEALOGY OF INTERACTIVE MUSIC 13

1.1 The augmentative exercise of interpretation 13

1.2 Democratisation of interpretation in arts 15

1.3 Technology and indeterminacy since process music 18

1.4 Literature review 20

1.5 Self-reflection in human-computer interaction 30

CHAPTER 2: REMOTENESS IN MUSIC TECHNOLOGY 36

2.1 Gaps in the interpretation of live digital content 37

2.2 Coherent validation of musical processes 37

2.3 From gestural surrogacy to interactional proximity 40

CHAPTER 3: A TOOL FOR CONSCIOUSNESS 44

3.1 Information technology empowering consciousness 45

3.2 Subjective motivation and musical coherence 47

3.3 Interactive music as a tool for the investigation of the self 50

CHAPTER 4: A BIOLOGICAL MODEL FOR HUMAN-COMPUTER INTERACTION 53

4.1 Human-machine “communication” 54

4.2 Consciousness in software agents 55

4.3 Comprehension of alterity in humans 57

4.4 Exchange of biological signs 62

4.5 Bio-logics: for a greater salience of computer-generated content 64

CHAPTER 5: SOFTWARE IMPLEMENTATIONS 68

5.1 VIVO 69

5.2 Energy variable 71

5.3 Audio/visual feedback loop 74

5.4 Embodiment in a wakeful music system 76

5.5 Adaptive Video Tracking 77

5.6 Open-content dynamic orchestration and Dynamic Rack 81

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5.7 Stochastic Energy Score 84

5.8 Map Interface 85

5.9 Collective musical embodiment 86

CHAPTER 6: CASE STUDIES 92

6.1 VIVOtube 93

6.2 Studio1 98

6.3 Interactive Music Group 102

6.4 Crescendo 104

6.5 Holzwege 107

6.6 IMG works: final notes 110

6.7 Velodrone 111

6.8 Invisible Cities 116

6.9 Collective 119

CONCLUSIONS 127

APPENDIX A: FEATURES OF THE SOFTWARE COMPONENTS 129

A1 - Adaptive Video Tracking: features 130

A2 - Dynamic Rack: features 132

A3 - Software features: additional video documentation 135

APPENDIX B: PARAMETERS DESCRIPTION 137

B1 - Main interface 138

B2 - Settings interface 142

B3 - Stochastic Energy Score: interface 145

APPENDIX C: TECHNICAL INFORMATION OF THE CASE STUDIES 148

C1 - VIVOtube: software components 149

C2 - Studio1: formalisation of the musical behaviours 149

C3 - IMG: general rules for improvisation 153

C4 - Crescendo: performative notes 154

C5 - Holzwege: improvisation notes 158

C6 - Collective: additional video documentation 161

REFERENCES LIST 165

6

Abstract

A new category of music-related software is proposed, implemented and tested through

creative practice. “Wakeful” musical instruments are those whose interaction listeners may

understand as musical. The term “wakeful” means here “sign-bearing”, in relation to the

potential of computers and human beings to interact in terms of exchange of signs. Wakeful

instruments may empower the users’ capacity for the interpretation of digital music in terms

of agency, cognition and communication. These users may experience a phenomenon of

collective musical embodiment, producing a shared form of intelligence, extended and

mediated by the computer, in music. VIVO is a computer-based interactive instrument of this

type, whose development is part of the research. It represents salience of action in terms of

energy and features video tracking for mapping quantity of motion to specific sub-ranges of

audio plug-ins parameters, dynamically. It includes an editor for stochastic scores and a single

graphic interface to control any plug-in, while monitoring the users’ and software agents’

activity. The present case studies cross-confirm the results by an analysis of the users’ and

listeners’ experiences and verbalisations and by an identification of the musical coherence in

the content, which the program generated.

7

Hypothesis

If a computer-based musical instrument sonically reflects some of the user’s salience of

action, he/she may have a greater chance of interpreting the structures generated by the

computer as music, as well as the listeners can do. The collective experience of multiple users

may produce a shared form of intelligence, in the music.

Introduction

Speed of computer computing allows for complex manipulation of data in ways a human

agent could not be capable. Musical improvisation requires musicians some effort and

learning time to interplay through a specific musical grammar, coherently. Instead, a

computer program could perform the task easily, if designed to operate appropriately.

However, the application of a grammar is not sufficient to create original ideas. While we may

consider algorithms that benefit from a user’s feedback of some sort to produce a more

interesting interplay than otherwise, the judgment about what is interesting or not is human.

However, while learning may grant some autonomy to the learners, users who delegate

content creation to computers partially renounce to such autonomy and can be spared only

from physical fatigue, as they still have to consume time in assisting the computer during the

decision-making process. Such integration of computers and human capabilities is a complex

issue. The study highlights in the literature review a property common to any interactive

music system: a form of interactional proximity embeds the user and the computer1.

The aim of the present research is to define a protocol for interactive music to allow

computer-based musical instruments to generate, autonomously from users’ assistance,

original sonic structures that human agents may recognise, as music. This new class of

interactive musical instruments adopts salience-based logics of interaction that are distinctive

to living beings. Such logics allow reflection of the users’ music interpretation, in the

computer outcome. “Wakeful” musical instruments are those, which implement this

protocol. The term “wakeful” means here “sign-bearing”, in relation to the potential of

computers and living beings, specifically humans, to interact in terms of exchange of signs.

1 To be discussed further since Section 1.4.

8

The application of the protocol may allow investigation of a shared and collaborative form of

intelligence. The research evaluates this chance by connecting together interpretation of

music and creative capacities of multiple users, self-reflecting in the music, through such

instruments.

While the mostly endorsed model for human-computer interaction frames it as similar to

human communication2, in human-computer interaction a communicative gap exists: while

computers treat any input as a different state of their own components3, humans interpret

information as a network of signs, as the present study will explore. This structural divergence

may hold human agents from attributing intentionality to computer outcomes, where at least

some of the characteristics denoting interpretation in living beings cannot be deduced from

the outcome4. The case studies confirmed this supposition: the audience did not recognise

the sonic structures “invented” by the computer as music.

In approaching a solution to scenarios like the above, the study proposes a theoretical

framework and a piece of software as an example for designing wakeful instruments. The

framework aims to operate human-computer interaction for music, within an audio/visual

feedback loop of action/perception based on a representation of salience as the energy that

the agents consume to act.

The present wakeful instrument analyses the user’s activity or data received from external

software. It may compute the image motion for different types of moving bodies: objects,

performers, performers acting on objects, and video images. The instrument calculates the

energy consumptions reflecting the salience of the activity, which the users can monitor. This

salience is mapped to audio processing and/or sound synthesis by the means of external

2 For example, in Robert Rowe’s definition of an interactive music system (see Section 1.4 and 4.1). 3 As bits, in digital computers. However, ‘[i]ncreasingly often, LSMs [Liquid State Machines], ESNs [Echo State Machines] and the more recently explored Backpropagation Decorrelation learning rule for RNNs [Recurrent Neural Networks] (Schiller and Steil 2005) are subsumed under the name of Reservoir Computing’ (Jaeger, 2007: n.p.), which offers an interesting perspective for future investigations of similarities between machines and living beings—for example in grammatical construction processing (Dominey, Hoen and Inui, 2006: 2088–2107), or Liquid Machine States investigation (Jones et al., 2007: 187–191). 4 While there is evidence that humans may attribute intentionality to the simplest of abstract animations (Blakemore et al., 2003: 1433–1441), recognition of the characteristics denoting interpretation leads to attribute stronger intentionality than otherwise. At least this can be stated for normal control subjects and patients without delusions of persecution, ‘[who] rated the relationship between the movement of the shapes as stronger in both mechanical and intentional contingent conditions than in non-contingent conditions’ (Blakemore et al., 2003: 1433). The present study investigates human intentionality, specifically in the sonic field.

9

audio plug-ins. Implementations of the above framework include a Dynamic Rack to

orchestrate audio signals, as well as a Stochastic Energy Score and a Map Interface to control

the analysis both of the users’ and of the instrument’s actions. These implementations are

part of the piece of software VIVO, a computer-based musical instrument, which the present

experimental work will show as matching the definition of wakefulness explored in the thesis.

Recalling previous research (Gadamer, 2004 [1960]), the present study outlines that for a

given human agent, the capacity for interpretation is aimed at explaining and applying

information to personal concerns and interests. In this process, consideration of previous

occurrences is implied, as are subjective experiences, acquired culture and broader biological

factors. The present investigation proposes a model for human interpretation, embodied in

the specific technology, as depending on the capacities for agency, cognition and

communication. The software implementation extends the musicians’ sonic creation capacity

and provides a feedback. This feedback can be useful to the users and the audience to explain

better the connections among the musical constructs5, to share such knowledge with others

and to increase applicability of the musical intentions. In terms of agency, cognition and

communication, users may achieve a different awareness of the relationship between the

self, the musical morphology and the empowering technology through which they interplay.

Redefining interactive music could have a great impact on knowledge in terms of

development of new musical forms and instruments and of a different understanding of the

human agent’s potential, which might be within reach. Evaluation of the case studies draws

from Gino Stefani’s analysis of semiosis in the human/music interface (Stefani, 1998), Mihaly

Csikszentmihalyi’s flow theory (Csikszentmihalyi, 2008 [1985]) and Aaron Antonovsky’s sense

of coherence (Antonovsky, 1987), as described in the Methodology.

Methodology

The investigation that led to the present research started in 2004. I published diverse texts6,

produced different music and developed various pieces of software. Each of these works

5 The notion of “musical construct” refers here to any sound or sequence of sounds considered as a whole (see Appendix D3). 6 The present dissertation draws from some of those texts (Paolizzo, 2006; 2010a; 2010b; 2011).

10

reached conclusions that sometimes confirmed, and sometimes contradicted, the previous

assumptions. Along this path, I abandoned some ideas, software implementations and

musical architectures in favour of others. However, in different degrees, all experimentation

was useful in pursuance of the research goals. A preliminary consideration preceded them.

Any technique or technology inevitably defines the content for which it is used; a

misunderstanding of the fundamental principles underlying a specific medium may lead the

musician or designer to cap or mislead their own expressive and creative capacity. This

concern led me to question how interactive music technology might affect the audience and

the users’ capacities in terms of agency, cognition and communication.

In consideration of the above, the proposed methodology is interdisciplinary. It draws from

cultural musicology, software development and music composition. In the present model,

formulation of hypotheses precedes and gives ground to the development of software

components based on the theorisations. I design and realise works of interactive music in

order to evaluate the hypotheses and promote them to working hypotheses, which the case

studies could verify. According to the theoretical tools of investigation offered by cultural

musicology, I carry out a critical analysis both of the audience’s and musicians’ responses and

of the creative outcomes. In the study, I connect this analysis with a theoretical dissertation

of the audience’s informally gathered observations. The method of evaluation envisages an

approach to art as theory, which benefits from the holistic attitude7 typical both of practice

and of experience in art, with the aim of developing and refining both theories and

implementations.

In my research, I approach holism in terms of a users’ perception of morphology-as-whole, in

order to evaluate coherence in the unit structures under analysis. These can either be musical

constructs, dynamics of interaction or works of interactive music. This approach of analysis

includes considering the subjective process of semiosis. In this sense, the methodology draws

7 It is useful to note that in philosophy of mind, ‘[f]unctionalism about content and meaning appears to lead to holism. In general, transitions among mental states and between mental states and behaviour depend on the contents of the mental states themselves. […] Other functionalists accept holism for “narrow content”, attempting to accommodate intuitions about the stability of content by appealing to wide content’ (Block, 1995: 329–330). Holism is not exempt from criticism. Samuel Guttenplan notes that while ‘holism has been most widely discussed in connection with both the contents of propositional attitudes and the meanings of linguistic constructions… no two speakers could ever mean the same thing by some given sentence, since it is almost certainly true that any two speakers will differ somewhere in their epistemic attitudes’ (Guttenplan, 1995b: 347).

11

and differs from Stefani’s research in an original way. Following his model for the analysis of

semiosis in the human/music interface, where the formulation of theories focuses on the

subjective experience of music (Stefani, 1998), the present research proposes a method to

formulate, evaluate and refine both theories and implementations through the creative

practice of interactive music.

As Luca Marconi points out, Stefani’s method does not include listening tests by observation,

devices or measurements of verbal and/or not verbal behaviours or other phenomena

occurring during the listening (Marconi, 2010: 1–4). Stefani adopts the method of an “orally

shared listening”8. In interactive music, interplay and listening intertwine and, therefore, in

my research I direct the users’ focus to the morphology by the nature of the interactive

experience itself. After the experience, I question the users about both the “quality” of the

music and of their interaction. “Quality” means here the comprehensibility, manageability

and meaningfulness of the musical constructs created and perceived in the experience, as

Antonovsky’s sense of coherence defines these concepts. I relate such a quality to the level

of subjectively perceived satisfaction and control in creating and exploring the music9, as

connected to Csikszentmihalyi’s notion of “flow”. Flow is a mental state, ‘where challenges

match skills, and in which people experience “optimal” states, are able to concentrate, to

forget time, and create new goals in a totally autonomous way, the so-called autotelic state

[(auto = “self” + telos = “goal”)]’ (Steels, as cited in Pachet, 2008: 10).

Users do not receive questions when they spontaneously express of experiencing a sense of

coherence, or if listening to the outcome and their musical behaviour in the interaction is

sufficient to draw conclusions about the investigated theories and software

implementations10. In collective experiences of interactive music based on the present model

of interpretation, the users’ musical morphology may become a language for the group self-

8 ‘Ascolto condiviso oralmente’. 9 Differently, Stefani’s method requires the listeners to focus on the subjective musical experience (the listener’s impression, which emerges during the listening) rather than on their description attributed to the music. Stefani gathers information about the experiences in the form of the participants’ verbalisations, in order to highlight similarities (Stefani, 1977: 23). 10 Stefani’s method aims at raising the listeners’ awareness about their musical proficiency as an ability similar to understand (and to produce) new sentences and discourses in a verbal language: ‘[ognuno dei partecipanti] possiede sulla musica una certa “competenza” analoga a quella che si ha per una lingua, ossia una capacità di capire (e produrre) frasi e discorsi sino allora non ancora sentiti (e prodotti)’ (Stefani, 1977: 21).

12

reflecting in the music. This commonality finds correspondence with the influence of shared

referents that Stefani aims at highlighting in the listening11 (Stefani, 1977: 23). While he aims

at increasing the awareness of the participants12 about the experts’ discourses, which may

influence these referents13 (Stefani, 1977: 26), in my research the users receive information

about their interaction by the software implementations. In the present case studies, I focus

such empirical methodology in result of the work started in 2004, gradually. Recent

theoretical research (Lutz, 2009: 63–67) first suggested the formal integration of these

collinear concepts from Antonovsky’s and Csikszentmihalyi’s researches. The present study is

an example of the empirical application of this integration14—which combines with other

theoretical tools, as mentioned.

In short, the present methodology allows the theorisation and application of interactive

music, in a specific co-presence of music and computer practices and aesthetics, as a tool for

the morphological investigation of human-computer interaction. Although the study focuses

on music and computer-based interactive music systems, concepts proposed within the

framework might apply to any human-computer interaction, where a computer generates or

transforms the content. In an attempt to favour coherence in interaction between humans

and software agents, I develop and test both VIVO and the framework by tailored works of

interactive music. Finally, broader resonances with historical and cultural ideas are sought by

interpreting fundamental notions and their aesthetics. From such a path the present

investigation will start.

11 ‘[…] dei rinvii o significati comuni che […] predominano sulle frange dell’interpretazione soggettiva’. 12 Stefani aims at achieving that through the followings: considerations about the sonic objects through listening (Stefani, 1979: 145–147, 1993a, 1993b); cultural investigation of the production process and historical background of the specific music works and of the composers’ ideas (Stefani, 1979: 147–149); different attitudes and ways of listening (Stefani, 1994: 13). 13 ‘[…] i contributi didattici che formulano o spiegano il sapere comune, gli apporti creativi che lo stimolano, gli occultamenti ideologici che se ne appropriano e lo camuffano da invenzione personale, il vaniloquio dovuto alla vanità o all’inettitudine’. 14 In 2009, Jonathan Luz could not find evidence of any publication formally suggesting such an integrative model (Lutz, 2009: 63–67). Similarly, I did not find any empirical method applying the model.

165

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