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Patterns of intuitionmusical creativ...

Nierhaus, Gerhard.

Patterns of intuitionmusical creativity in the light of algorithmic composition /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Patterns of intuitionedited by Gerhard Nierhaus.
Reminder of title:	musical creativity in the light of algorithmic composition /
other author:	Nierhaus, Gerhard.
Published:	Dordrecht :Springer Netherlands :2015.
Description:	viii, 421 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computer composition.
Online resource:	http://dx.doi.org/10.1007/978-94-017-9561-6
ISBN:	9789401795616 (electronic bk.)

Patterns of intuitionmusical creativity in the light of algorithmic composition /
Patterns of intuitionmusical creativity in the light of algorithmic composition /[electronic resource] :edited by Gerhard Nierhaus. - Dordrecht :Springer Netherlands :2015. - viii, 421 p. :ill., digital ;24 cm.

Outline of the compositional structure(s) to be investigated -- The algorithms/procedures used -- Findings -- Improvisation in Trees -- Electronic Music for an Acoustic Piano -- Forbidden Melodies -- The Semantics of a String Quartet -- Comments from renowned scientists from related research areas of Algorithmic Composition, Musicology, Artistic Research, Creativity.

The present book is the result of a three year research project which investigated the creative act of composing by means of algorithmic composition. Central to the investigation are the compositional strategies of 12 composers, which were documented through a dialogic and cyclic process of modelling and evaluating musical materials. The aesthetic premises and compositional approaches configure a rich spectrum of diverse positions, which is reflected also in the kinds of approaches and methods used. These approaches and methods include the generation and evaluation of chord sequences using genetic algorithms, the application of morphing strategies to research harmonic transformations, an automatic classification of personal preferences via machine learning, and an application of mathematical music theory to the analysis and resynthesis of musical material. The second part of the book features contributions by Sandeep Bhagwati, William Brooks, David Cope, Darla Crispin, Nicolas Donin, and Guerino Mazzola. These authors variously consider the project from different perspectives, offer independent approaches, or provide more general reflections from their respective research fields.

ISBN: 9789401795616 (electronic bk.)

Standard No.: 10.1007/978-94-017-9561-6doiSubjects--Topical Terms:

256933
Computer composition.

LC Class. No.: MT56

Dewey Class. No.: 781.34

Patterns of intuitionmusical creativity in the light of algorithmic composition /
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245 0 0 $a Patterns of intuition $h [electronic resource] : $b musical creativity in the light of algorithmic composition / $c edited by Gerhard Nierhaus.
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300 $a viii, 421 p. : $b ill., digital ; $c 24 cm.
505 0 $a Outline of the compositional structure(s) to be investigated -- The algorithms/procedures used -- Findings -- Improvisation in Trees -- Electronic Music for an Acoustic Piano -- Forbidden Melodies -- The Semantics of a String Quartet -- Comments from renowned scientists from related research areas of Algorithmic Composition, Musicology, Artistic Research, Creativity.
520 $a The present book is the result of a three year research project which investigated the creative act of composing by means of algorithmic composition. Central to the investigation are the compositional strategies of 12 composers, which were documented through a dialogic and cyclic process of modelling and evaluating musical materials. The aesthetic premises and compositional approaches configure a rich spectrum of diverse positions, which is reflected also in the kinds of approaches and methods used. These approaches and methods include the generation and evaluation of chord sequences using genetic algorithms, the application of morphing strategies to research harmonic transformations, an automatic classification of personal preferences via machine learning, and an application of mathematical music theory to the analysis and resynthesis of musical material. The second part of the book features contributions by Sandeep Bhagwati, William Brooks, David Cope, Darla Crispin, Nicolas Donin, and Guerino Mazzola. These authors variously consider the project from different perspectives, offer independent approaches, or provide more general reflections from their respective research fields.
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