Algorithmic Composition

Paradigms of Automated Music Generation

Author: Gerhard Nierhaus

Publisher: Springer Science & Business Media

ISBN: 3211755403

Category: Mathematics

Page: 287

View: 8918

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Algorithmic composition – composing by means of formalizable methods – has a century old tradition not only in occidental music history. This is the first book to provide a detailed overview of prominent procedures of algorithmic composition in a pragmatic way rather than by treating formalizable aspects in single works. In addition to an historic overview, each chapter presents a specific class of algorithm in a compositional context by providing a general introduction to its development and theoretical basis and describes different musical applications. Each chapter outlines the strengths, weaknesses and possible aesthetical implications resulting from the application of the treated approaches. Topics covered are: markov models, generative grammars, transition networks, chaos and self-similarity, genetic algorithms, cellular automata, neural networks and artificial intelligence are covered. The comprehensive bibliography makes this work ideal for the musician and the researcher alike.
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Machine Learning and Music Generation

Author: José M. Iñesta,Darrell C. Conklin,Rafael Ramírez-Melendez,Thomas M. Fiore

Publisher: Routledge

ISBN: 1351234528

Category: Mathematics

Page: 112

View: 8445

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Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.
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The Oxford Handbook of Algorithmic Music

Author: Alex McLean,Roger T. Dean

Publisher: Oxford University Press

ISBN: 0190227001

Category: Music

Page: 648

View: 516

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With the ongoing development of algorithmic composition programs and communities of practice expanding, algorithmic music faces a turning point. Joining dozens of emerging and established scholars alongside leading practitioners in the field, chapters in this Handbook both describe the state of algorithmic composition and also set the agenda for critical research on and analysis of algorithmic music. Organized into four sections, chapters explore the music's history, utility, community, politics, and potential for mass consumption. Contributors address such issues as the role of algorithms as co-performers, live coding practices, and discussions of the algorithmic culture as it currently exists and what it can potentially contribute society, education, and ecommerce. Chapters engage particularly with post-human perspectives - what new musics are now being found through algorithmic means which humans could not otherwise have made - and, in reciprocation, how algorithmic music is being assimilated back into human culture and what meanings it subsequently takes. Blending technical, artistic, cultural, and scientific viewpoints, this Handbook positions algorithmic music making as an essentially human activity.
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Patterns of Intuition

Musical Creativity in the Light of Algorithmic Composition

Author: Gerhard Nierhaus

Publisher: Springer

ISBN: 9401795614

Category: Computers

Page: 421

View: 7321

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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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The Haskell School of Music

From Signals to Symphonies

Author: Paul Hudak,Donya Quick

Publisher: Cambridge University Press

ISBN: 1108416756

Category: Computers

Page: 420

View: 7640

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Learn functional programming and the Haskell programming language through algorithmic music composition and virtual instrument design.
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International Electronic Conference on Computer Science

Author: Theodore E. Simos,George Psihoyios

Publisher: American Inst. of Physics

ISBN: 9780735405905

Category: Science

Page: 440

View: 1889

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The aim of IeCCS 2007 is to bring together leading scientists of the international Computer Science community and to attract original research papers of very high quality. The topics to be covered include (but are not limited to): Numerical Analysis, Scientific Computation, Computational Mathematics, Mathematical Software, Programming Techniques and Languages, Parallel Algorithms and its Applications, Symbolic and Algebraic Manipulation, Analysis of Algorithms, Problem Complexity, Mathematical Logic, Formal Languages, Data Structures, Data Bases, Information Systems, Artificial Intelligence, Expert Systems, Simulation and Modeling, Computer Graphics, Software Engineering, Image Processing, Computer Applications, Hardware, Computer Systems Organization, Software, Data, Theory of Computation, Mathematics of Computing, Information Systems, Computing Methodologies, Computer Applications, Computing Milieu (see http://www.ieccs.net/topics.htm).
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