The Development of Intelligent Drum Machines Using Cartesian Genetic Programming Initial Report
University of York
Department of Electronics
Third year Beng Preliminary Report 2012/13
The Development of Intelligent Drum Machines using Cartesian Genetic Programming
Student ID (Y6385813)
Work For: Julian Miller
Due Monday 11th February 2013
Abstract
Modern day electronic instruments often produce and perform unrealistic music lacking the subtleties introduced by a real life musician. Other than recording a musician or meticulously editing an audio track there is no quick and easy way to replicate this natural feel. Furthermore the factor that adds this organic quality to music cannot always easily be identified, we may not know why we prefer one piece to another only that we prefer it thus the general rules of art cannot be defined. This report addresses the application of Cartesian Genetic Programming; a process based on natural selection to create an intelligent drum machine which alters existing tracks in a way that makes them sound more natural, human and organic over time.
Contents
1. Introduction…………………………………………………………………………………………..……………1
2. Literature Review…………….....……………………………………………………………………………...2
2.1 What Makes A Rhythm “Groove”…………………………………………………………………….2
2.2 Automatic Composition………………………………………………………………………………….4
2.3 Genetic Programming……………….…………………………………………………………………...5
2.4 MIDI…………………………………..………………………………………………...……….………………..8
3. The Experiment....…………...………………………….……………………………………………………….9
3.1 Proposition and Objectives…………………………………………………………………………….9
3.2 Using Cartesian Genetic Programming and MIDI………………………………………...11
3.3 General Approach and Project Plan………………………………………………………….…13
4. References……………………………………………………………………………………………………..…15
5. Bibliography…………………………………………………………………………………………………….16
1. Introduction
A musician’s need to express their musical ideas in a way that is both acoustically pleasing and comfortable for whom ever is using it cannot always be
Department of Electronics
Third year Beng Preliminary Report 2012/13
The Development of Intelligent Drum Machines using Cartesian Genetic Programming
Student ID (Y6385813)
Work For: Julian Miller
Due Monday 11th February 2013
Abstract
Modern day electronic instruments often produce and perform unrealistic music lacking the subtleties introduced by a real life musician. Other than recording a musician or meticulously editing an audio track there is no quick and easy way to replicate this natural feel. Furthermore the factor that adds this organic quality to music cannot always easily be identified, we may not know why we prefer one piece to another only that we prefer it thus the general rules of art cannot be defined. This report addresses the application of Cartesian Genetic Programming; a process based on natural selection to create an intelligent drum machine which alters existing tracks in a way that makes them sound more natural, human and organic over time.
Contents
1. Introduction…………………………………………………………………………………………..……………1
2. Literature Review…………….....……………………………………………………………………………...2
2.1 What Makes A Rhythm “Groove”…………………………………………………………………….2
2.2 Automatic Composition………………………………………………………………………………….4
2.3 Genetic Programming……………….…………………………………………………………………...5
2.4 MIDI…………………………………..………………………………………………...……….………………..8
3. The Experiment....…………...………………………….……………………………………………………….9
3.1 Proposition and Objectives…………………………………………………………………………….9
3.2 Using Cartesian Genetic Programming and MIDI………………………………………...11
3.3 General Approach and Project Plan………………………………………………………….…13
4. References……………………………………………………………………………………………………..…15
5. Bibliography…………………………………………………………………………………………………….16
1. Introduction
A musician’s need to express their musical ideas in a way that is both acoustically pleasing and comfortable for whom ever is using it cannot always be
References: [1] Miller J. F., Thomson P. Cartesian Genetic Programming. Proceedings of the 3rd European Conference on Genetic Programming. Springer LNCS 1802 (2000) 121-132. [2] Koza, John R. "Genetic programming as a means for programming computers by natural selection." Statistics and Computing 4(2) (1994): 87-112. [3] Larranaga, Pedro, et al. "Genetic algorithms for the travelling salesman problem: A review of representations and operators." Artificial Intelligence Review 13(2 )(1999): 129-170. [4] David, B. Fogel. "Applying evolutionary programming to selected traveling salesman problems." Cybernetics and systems 24(1) (1993): 27-36. [5] Ashmore, Laurence, and J. Miller. "Evolutionary Art with Cartesian Genetic Programming." Technical Online Report (2004). [6] Wikipedia (2013) MIDI. [online] Site: http://en.wikipedia.org/wiki/MIDI [Accessed: 7 Feb 2013]. [7] Harding, Simon L., Julian F. Miller, and Wolfgang Banzhaf. "Self-modifying cartesian genetic programming." Cartesian Genetic Programming (2011): 101-124. [8] Costelloe, Dan, and Conor Ryan. "Genetic programming for subjective fitness function identification." Genetic Programming (2004): 259-268. [9] Senaratna, Nuwan I. "AUTOMATIC MUSIC COMPOSITION USING A TREE OF INTERACTING EMERGENT SYSTEMS." (2006). [10] Tokui, Nao, and Hitoshi Iba. "Music composition with interactive evolutionary computation." Proceedings of the 3rd international conference on generative art. Vol. 17. No. 2. 2000. [14] Johanson, Brad, and Riccardo Poli. "GP-music: An interactive genetic programming system for music generation with automated fitness raters."Genetic Programming 1998: Proceedings of the Third Annual Conference. 1998. [15] John A. Maurer, A history of Algorithmic Composition (1999) Site: https://ccrma.stanford.edu/~blackrse/algorithm.html [16] Friberg, Anders, and Andreas Sundström. "Swing ratios and ensemble timing in jazz performance: Evidence for a common rhythmic pattern." Music Perception19.3 (2002): 333-349. [17] Wikipedia (2013), Groove (music) [online] Site: http://en.wikipedia.org/wiki/Groove_(music) [Accessed: 1 Feb 2013]. Mitchell Melanie. “An Introduction To Genetic Algorithms”. 1st ed. MIT press (1998). Butler, Mark Jonathan. “Unlocking the groove: rhythm, meter, and musical design in electronic dance music”. Indiana University Press, (2006). A. Hunt, “Your Research Project: How to Manage It”. New York: Routledge, 2005.