Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben

2007 | Buch

An Introduction to Evolutionary Computing for Musicians Kapitel lesen Erstes Kapitel lesen

Evolutionary Computer Music

herausgegeben von: Eduardo Reck Miranda, MSc, PhD, John Al Biles, BA, MS, PhD

Verlag: Springer London

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Einloggen, um Zugang zu erhalten
insite
SUCHEN

Über dieses Buch

Musicians, perhaps more than any other class of artists, have always been acutely aware of the scientific developments of their time. From the discovery almost three thousand years ago of the direct relationship between the pitch of a note and the length of a string or pipe, to the latest computer models of human musical cognition and intelligence, musicians have always looked to science to provide new and challenging ways to study and compose music. With the great scientific advances being made in the field of evolutionary biology, from new insights into the origins of humans and other species to complete mappings of the genes that control our growth and development, a new approach to the study of music is emerging: the evolutionary computation approach. This book features chapters on the interplay between Evolutionary Computation and Music by leading pioneers in the field.

Inhaltsverzeichnis

Frontmatter
1. An Introduction to Evolutionary Computing for Musicians
Abstract
The aim of this chapter is twofold: to provide a succinct introduction to evolutionary computing, outlining the main technical details, and to raise issues pertinent to musical applications of the methodology. Thus this chapter should furnish readers with the necessary background needed to understand the remaining chapters in this volume as well as open up a number of important themes relevant to this collection.
PHIL HUSBANDS, PETER COPLEY, ALICE ELDRIDGE, JAMES MANDELIS
2. Evolutionary Computation for Musical Tasks
Abstract
If the preceding chapter was an introduction to evolutionary computation (EC) for musicians, this chapter is intended as an introduction to music as a problem domain for EC researchers. Since we cannot hope to provide even a bare-bones treatise on music appreciation, much less music theory, we assume that the reader is at least somewhat familiar with music, if not as a producer, at least as a consumer. We will start by trying to define some musical terms to work with, including ‘music’ itself, which will lead us to a brief excursion into human-computer interaction as a metaphor for musical performance. We will then conduct an informal task analysis of music to define the tasks musicians perform and survey how EC has been applied to facilitate (or obfuscate, in some cases) the performance of those tasks. We will then summarize the various approaches that have been taken in representation, fitness and genetic operators.
JOHN A. BILES
3. Evolution in Digital Audio Technology
Abstract
Replicating musical instruments is a classic problem in computer music.Asystematic collection of instrument designs for each of the main synthesis methods has long been the El Dorado of the computer music community. Here is what James Moorer, the pioneering computer music researcher at Stanford University and later director of the audio project at Lucasfilm, had to say about it (Roads 1982):
ANDREW HORNER
4. Evolution in Creative Sound Design
Abstract
… But what if the synthesizer just ‘grew’ programs? If you pressed a ‘randomize’ button which then set any of the thousand ‘black-box’ parameters to various values and gave you sixteen variations. You listen to each of those and then press on one or two of them—your favourite choices. Immediately, the machine generates 16 more variations based on the ‘parents’ you’ve selected. You choose again. And so on. The attraction of this idea is that one could navigate through very large design spaces without necessarily having any idea at all of how any of these things were being made. (Eno 1996)
PALLE DAHLSTEDT
5. Experiments in Generative Musical Performance with a Genetic Algorithm
Abstract
It is commonly agreed in the context of Western tonal music that expression is conveyed by delicate deviations of the notated musical score, through shaping physical parameters of performance, such as timing, loudness, tempo and articulation. Expressive music performance research is aimed at establishing why, where and how these deviations take place in a piece of music. Interestingly, even though there are many commonalities in performance practices, these deviations can vary substantially from performance to performance, even when a performer plays the same piece of music more than once.
QIJUN ZHANG, EDUARDO R. MIRANDA
6. Composing with Genetic Algorithms: GenDash
Abstract
This chapter describes the author’s ongoing work with evolutionary computation in the composing of ‘art’ or ‘concert’ music. Over the course of many years, the author has written and rewritten a computer program called GenDash that employs evolutionary computation. GenDash has been used to help compose pieces ranging from works scored for solo human speaker to string quartets to orchestral works to pieces for instrumentalist and electronic computer music to operas.
RODNEY WASCHKA II
7. Improvizing with Genetic Algorithms: GenJam
Abstract
Imagine you are walking down the street past a coffeehouse that features live jazz. From inside the coffeehouse you hear a jazz quartet begin to play a tune. As you pause outside to listen, it sounds like a tenor sax player backed up by a standard jazz trio of piano, bass and drums. You recognize the tune as John Coltrane’s Giant Steps as the tenor player plays the song’s original melody in the first chorus of the tune. Once this ‘head’ chorus is complete, everyone continues playing in the second chorus, but the tenor player plays a melody that is decidedly not the original melody of the song, switching from the half note rhythm of the original melody to a more active eighth-note-based rhythm. The piano, bass, and drums seem to be playing things that are similar to what they played on the first chorus, except that the bass player is playing a note on every beat instead of roughly every other beat, and the drummer is more active and assertive. This continues for four more improvized choruses, at which point the tenor player begins playing the original melody of the tune again. After this reprise of the tune’s head, there is a brief coda and the tune ends.
JOHN A. BILES
8. Cellular Automata Music: From Sound Synthesis to Musical Forms
Abstract
Cellular automata (CA) are tools for computational modelling widely used to model systems that change some feature with time. They are suitable for modelling dynamic systems in which space and time are discrete, and quantities take on a finite set of discrete values. CA are highly suitable for modelling music: music is fundamentally time-based and it can be thought of as a system in which a finite set of discrete values (e.g. musical notes, rhythms, etc.) evolve in space and time.
EDUARDO R. MIRANDA
9. Swarming and Music
Abstract
Music is a pattern of sounds in time. A swarm is a dynamic pattern of individuals in space. The structure of a musical composition is shaped in advance of the performance, but the organization of a swarm is emergent, without pre-planning. What use, therefore, might swarms have in music?
TIM BLACKWELL
10. Computational Evolutionary Musicology
Abstract
The beginning of Chapter 2 offered a sensible definition of music as temporally organized sound. In the broader sense of this definition, one could arguably state that music is not uniquely human. A number of other animals also seem to have music of some sort. Complex vocalizations can be found in many birds (Marler and Slabbekoorn 2004), as well as in mammals such as whales (Payne and McVay 1971) and bats (Behr and von Helversen 2004). In a chapter suggestively entitled ‘Zoomusicologie’ in the book Musique, Mythe, Nature ou Les Dauphins d’Arion, Mâche (1991) presents an interesting discussion on the formal sophistication of various birdcalls. Recently Holy and Guo (2005) demonstrated that the ultrasonic vocalizations that male mice produce when they encounter female mice or their pheromones have the characteristics of song. What is intriguing is that primates who are close related to humans are not as ‘musical’ as those mammals that are far more distantly related to us. This intriguing fact suggests that music might have evolved independently among various types of animals, at various degrees of sophistication. In this context, it would be perfectly plausible to suggest the notion that robots might also be able to evolve music.
EDUARDO R. MIRANDA, PETER M. TODD
Backmatter
Metadaten
Titel
Evolutionary Computer Music
herausgegeben von
Eduardo Reck Miranda, MSc, PhD
John Al Biles, BA, MS, PhD
Copyright-Jahr
2007
Verlag
Springer London
Electronic ISBN
978-1-84628-600-1
Print ISBN
978-1-84628-599-8
DOI
https://doi.org/10.1007/978-1-84628-600-1

Neuer Inhalt

    Bildnachweise