Generative
Musical Improvisation For Participants With All Kinds of Musical Backgrounds
M.Koray Tahiroglu
Media Lab, University of Art and Design Helsinki,
Finland
e-mail: ktahirog@uiah.fi
Abstract
This paper presents a generative musical improvisation process. During
the moment of playing, there is a contact between the sound created by the
performer and the sound generated by the interactive system. The improvisation
turns into a continuous composition as long as a performer takes an active role
in the performance. An important goal of the performance is to provide a
situation where a participant of the performance can experience a free
collective musical improvisation. It is a generative musical improvisation
environment for participants with all kinds of musical backgrounds.
1.Introduction
In the history of music sequencing, from the appearance of the first
automatic instrument Aeoles [1], in the early second century BC, up to this
time, there have always been new ideas coming forth on creating and developing
new musical instruments, styles and theories. There is a cross influence
relation between technology and existing music forms in any timepiece. Although
technology does not invent a new form of music, it opens up new possibilities
for musicians to expend their abilities to offer new musical values.
Non-traditional and computer based interactive systems have been potential
environments for these kind of possibilities in music [2]. Early examples of computer
generated music compositions are limited by the requirement of computer
technology, however they encouraged musicians to compose computer programs to
create models for their compositions. Computers have been affording composers a
high level of control over the evolution and the variation of organizing
sounds.
Computers, by framing a ground for generative music, free the composers
from a note-by-note composition. Without worrying about the actual note and the
existing musical structures, computers allow composers to concentrate more on
the process. This creates an identical characteristic of generative music,
which concerns itself more with the process rather than a predefined outcome.
Developing techniques for transforming the process into randomness or
into a concept of chance, constructed different models in generative music
compositions. Statistics have been used to derive musical composition from
mathematics and logic. Xenakis, a major figure in the area of algorithmic
composition, developed stochastic technique with his compositions [3]. His
approach was based on random generation and probability theory, which is used
to generate material in a number of ways. Statistical analysis has been used as
a modeling technique in most of the algorithmic music compositions. The
interactive system of the performance is using random walk, drunk walk
probability method to generate notes in its algorithmic structures. In this method, information is linked
together in a series of situations based on the probability of the sequences.
Random walk, drunk walk, has similar probability structure as Markov chain
process. Markov chains based on the sequences of random variables in which the
future variable is determined by the present but is independent of the way in which
the present state occurred from its predecessors [4]. Probability is the core
statement of the decisions in Markov chains sequences.
2. Role of Improvisation
During a collective musical improvisation there is a continues
communication between musicians. The interactive system that runs in the
performance creates this communication with performer on the listen and respond
ground. This two-way interaction supports the improvisation’s beautiful and
ever-changing identity and brings the unexpected beauty on the stage.
When it comes to music, the word improvise
can be defined as performing without a musical score, or producing sound in a
performance without preparation. It is a way of playing that gives unexpected
results. Karlheinz Essl, Austrian composer, improviser and performer, describes
the real time in which improvisation takes place, is passing by where one has
to follow a certain way which might have been thought about before or which
turns out to be negotiable during the improvisation [5]. One must be
continuously conscious of references; what has happened before, how can this be
developed further? At the same time, during a collective musical improvisation
there is a continues activity, such as exploring new sequence of sounds and
listening consciously [6]. Responding immediately and spontaneously to one
other’s playing creates the process of communication in free collective
improvisation. Within theses immediate responses there is also conscious
awareness of how the sound is connected to other musician’s sound. Free
collective improvisation, which is based on formless conversation, is a
dialogue between musicians. No one knows where the conversation will go. The
outcome of a free collective improvisation is unpredictable. This makes it
possible to link performance practice of a free improvisation to any generative
work process. Free improvisation concerns itself more with creating the
dialogue between musicians rather than predefined performance outcome.
The task of the interactive system that runs during the generative
musical improvisation performance is to create this dialogue in real time
between a performer and the system. In this context performer’s actions,
musical outputs, affect the interactive systems outputs and also interactive
system’s outputs affect performer’s outputs. Performer’s musical actions are
the needed input information for the system to generate notes, rhythms, to
assign tempo changes and also to suggest scales to be followed during the
improvisation. Performer improvises and the interactive system responds by
improvising. It is a collective improvisation performance.
Involving the work of computer in
the decision making process makes it possible to explore more about the machine
aesthetics in this performance. Human-computer interaction is the main building
block of this improvisation process.
Figure1. Interactive
system of the From Me to Us installation was
developed further to be a generative musical improvisation tool for this
performance [2].
3. Algorithm
“Everything around us can be represented and understood through
numbers.” Max Cohen [7]
The musicians of ancient Greek built their musical systems upon the
theoretical applications of numbers and various mathematical properties derived
from nature [8]. These properties were the formalisms, or algorithms. These
early algorithms did not involve the musician to be entirely removed from the
decision making process of the composition. However musical systems of
intervals and modes which are based on the concept of the “Music of the
Spheres” are undoubtedly important historically in music for its leaning
towards formal non-human processes.
The Webster’s College Dictionary defines algorithm as a set of rules for
solving a problem in a finite number of steps, in order to find the greatest
common divisor. A sequence of steps designed for programming a computer to
solve a specific problem [8]. In musical applications, algorithms may be
thought of as procedures that test potential compositional material for its
suitability within the given context. With this definition of algorithm, an
algorithmic composition can be described as the application of a well-defined
algorithm to the process of composing music [9].
During the past decades various interactive systems have been
implemented in computer generated music applications. These implementations are
constructed on their suitable algorithmic music theories. Music theories have
their individual identities in relation with their time and application
systems, however there are similarities and relations between each other as
well. Their evaluation may even be built on the earlier efforts of other
implementation. Robert Rowe identifies the applied systems’ similarities and
relations by developing a classification of interactive systems [10]. The
computational methods of classification, which are in touch with this
performance, are the interactive computer response methods. Interactive system
is constructed by using Pure Data environment.
Pure Data is a freeware graphical programming
environment for real-time audio and graphical processing. Miller Puckette has
been actively developing Pure Data computer music environment. Pure Data was
written for multiplatform from the beginning. It is open source software that
can be downloaded, free for any use and development [11]. It is a work in progress.
Electric guitar that gives two outputs has been
chosen as a performer’s instrument in order to communicate with the system.
Analog output directly goes through chorus and over-drive effect processors. Second
output goes through MIDI guitar interface where analog sounds are transformed
into MIDI information and connected directly to the computer. By filtering and
analyzing the musical information that comes from the performer, computer
system runs three major decision making units. Tempo-rhythm generator, note
generator and record-sample units.
Note generator is a part of a system that follows the player
as well as a part of a response technique method. Performer defines the musical
structure that will be followed during the performance, however the system also
randomly proposes the certain scales. Randomness is the core statement of the
decisions in the system’s response process. Performer’s musical inputs are
analyzed in order to give immediate response
to a response to create a free collective improvisation process.
The random outcomes in the performance are determined so
that the generated notations will not be dependent on any predefined structure.
Even though certain scales are followed, there is no predefined structure
concerning the order of notes that the system generates. No two performances are identical. Following the scales with non-predefined notes creates the
controlled random identity of the interactive system.
4. Conclusion
The performance provides a situation where a participant of the
performance can experience a free collective musical improvisation. It is a
generative musical improvisation environment for participants with all kinds of
musical backgrounds. The performance brings together the ever-changing musical
identity of a free improvisation and the work of computer in the generative
process.
5. References
[1]
Muro, Don and Purse, Bill. 2000. TI:ME Course 2A Advanced Sequencing, course material. Available from:
http://courses.wcupa.edu/frichmon/time2a/sequencing2a.pdf.
[2]
Tahiroglu, M.Koray. From Me to Us, a computer generated music installation. In
Proceedings of the Participatory Design Conference (PDC '04), Vol 2, Toronto,
Canada, July 27-31, 2004, CPSR, P.O. Box 717, Palo Alto, CA 94302, p12, 2004.
[3]
Fonseka, Joseph Rukshan 2000. Musical Agents. Thesis
(Master of Science). Monash University. Available from:
http://yoyo.cc.monash.edu.au/~ruki/downloads/Thesis.doc.
[4]
Franz, David M. 1998. Markov Chains as Tools
for Jazz Improvisation Analysis. Thesis
(Master of Science). Virginia Polytechnic Institute and State University. Available
from:
http://scholar.lib.vt.edu/theses/available/etd-61098-131249/unrestricted/dmfetd.pdf
[5]
Essl, Karlheinz 2002. Improvisation on "Improvisation",
ed. Hauser, Jack . Available from:
http://www.essl.at/bibliogr/improvisation-e.html.
[6]
Nunn, Tom. Wisdom
of The Impulse. On the Nature of Musical Free Improvisation. 1998 (publ. by
author), pdf version (IIMA) 2004.
[7]
Pi . Film. Directed by Darren ARONOFSKY. USA, 1998
[8]
Maurer, John A. 1999. A Brief History of Algorithmic Composition. Paper. Available
from: http://ccrma-www.stanford.edu/~blackrse/algorithm.html.
[9]
Jacob, Bruce L. Algorithmic Composition As A Model of Creativity. Organised Sound,
vol. 1, no. 3; Special issue on algorithmic composition. Cambridge University
Press, December 1996.
[10]
Rowe, Robert. Interactive Music Systems : Machine Listening and Composing.
Cambridge, Massachusetts: The MIT Press, 1993.
[11] Pure
Data Community Site is available from : http://www.puredata.org/