A computational framework for aesthetical navigation in musical search space

Paper presented at 3rd AISB symposium on computational creativity, AISB 2016, 4-6th April, Sheffield. Abstract. This article addresses aspects of an ongoing project in the generation of artificial Persian (-like) music. Liquid Persian Music software (LPM) is a cellular automata based audio generator. In this paper LPM is discussed from the view point of future potentials of algorithmic composition and creativity. Liquid Persian Music is a creative tool, enabling exploration of emergent audio through new dimensions of music composition. Various configurations of the system produce different voices which resemble musical motives in many respects. Aesthetical measurements are determined by Zipf’s law in an evolutionary environment. Arranging these voices together for producing a musical corpus can be considered as a search problem in the LPM outputs space of musical possibilities. On this account, the issues toward defining the search space for LPM is studied throughout this paper

The Faculty Notebook, September 2016

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost

Support materials for the use of Pygraphic\u27s The music writer in the beginning music theory class at Sacramento High School Visual and Performing Arts Center : in partial fulfillment ...

The objective of this project was to develop the necessary materials to facilitate the use of The Music Writer in the music theory class of Sacramento High School’s Visual and Performing Arts Center. The materials were designed to correct the deficiencies in the programs’ documentation, and include tutorials that sequentially introduce beginning students to the basic features of the program. The course is designed to teach skills and techniques in music fundamentals while providing students with practical experience involving the current technological advances in the field. These materials will enable the students to utilize professional level software in their study of basic music theory. Specifically, they will be able to use the program to write a simple diatonic melody, which has been composed as an assignment for the course

Algorithmic music composition: a survey

This paper surveys some of the methods used for algorithmic composition and their evolution during the last decades. Algorithmic composition was motivated by the natural need to assist and to develop the process of music creation. Techniques and applications of algorithmic composition are broad spectrum, ranging from methods that produce entire works with no human intervention, up to methods were both composer and computer work closely together in real-time. Common algorithms used for music composition are based in stochastic, deterministic, chaotic and artificial intelligence methods.N/

MU_PSYC : Algorithmic music composition with a music-psychology enriched genetic algorithm

Recent advancement of artificial intelligence (AI) techniques have impacted the field of algorithmic music composition, and that has been evidenced by live concert performances wherein the audience reportedly often could not tell whether music was composed by machine or by human. Among the various AI techniques, genetic algorithms dominate the field due to their suitability for both creativity and optimization. Many attempts have been made to incorporate rules from traditional music theory to design and automate genetic algorithms. Another popular approach is to incorporate statistical or mathematical measures of fitness. However, these rules and measures are rarely tested for their validity. This thesis is aimed at addressing the above limitation and hence paving the way to advance the field towards composing human-quality music. The basic idea is to look beyond this constrained set of traditional music rules and statistical/mathematical methods towards a more concrete foundation. We look to a field at the intersection of musicology and psychology, referred to as music-psychology. To demonstrate our proposed approach, we implemented a genetic algorithm exclusively using rules found in music-psychology. An online survey was conducted testing the quality of our algorithm’s output compositions. Moreover, algorithm performance was analyzed by experimental study. The initial results are encouraging and warrant further research. The societal implications of our work and other research in the field are also discussed

Computer -Assisted Instruction and Sequencing Within the Studio: a Focus on Halsey Stevens\u27 Sonata for Trumpet and Piano

The teaching of solo literature in the context of studio trumpet instruction has always presented personal challenges, especially when that literature includes a variety of mixed meter, subito tempo, and dynamic changes. Consistent aid from a metronome and tuner has for generations facilitated the dedicated musician, yet these devices are obviously limited by the student\u27s dedication, receptivity, and innate talent. I conversely propose that by introducing computer assisted instruction within the confines of the private studio, the students\u27 musical ability will be enhanced as will the pupils\u27 consistent practice regiment. The introductory segment of Chapter 1 provides an extremely truncated synopsis regarding the history of MIDI, examples of current MIDI applications within the studio, and the justification thereof. Chapter 2 encompasses the specific procedures used to accomplish computer assisted accompaniment in the studio, while relevant topics such as equipment, analysis of the Stevens\u27 Sonata For Trumpet and Piano, and programming/editing procedures are comparatively addressed. The processes of programming and editing comprise much of this chapter, since these components form an integral function within the electronic music studio. The third chapter exists as a compendium of contemporary practices regarding CIA (computer assisted instruction), with the remaining passages comprising a conclusion. It is my intent that production of this document will inform other studio instructors of the value of introducing technology to students, their quest furthered with the inclusion of a relevant guide needed to compile and construct a successful computer assisted studio

A Functional Taxonomy of Music Generation Systems

Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical tasks targeted by different machines and the degree to which they succeed remain open questions. We present a functional taxonomy for music generation systems with reference to existing systems. The taxonomy organizes systems according to the purposes for which they were designed. It also reveals the inter-relatedness amongst the systems. This design-centered approach contrasts with predominant methods-based surveys and facilitates the identification of grand challenges to set the stage for new breakthroughs.Comment: survey, music generation, taxonomy, functional survey, survey, automatic composition, algorithmic compositio

Evolutionary perspectives in computer music

This paper presents a brief overview of music evolution - western and non-western music - from its genesis to serialism and the Darmstadt school. Some mathematical aspects of music are then presented and confronted with music as a form of art. Some questions follow: are these two (very) distinct aspects compatible? Can computers be of real help in automatic composition? Evolutionaty Algorithms (EAs) - Genetic Algorithms (GAs), Genetic Programming (GP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) - are then introduced and some results of GAs and GPs application to music generation are analysed. Variable fitness functions and PSO application seems a promising way to explore. However, what output should be envisaged? Should we expect that computer music sounds as human music, or should we look for a totally different way to explore and listen? How far can go computer creativity and in what direction?N/

Genetic music

Algorithmic music composition has long been an active area of research in computer science, but the need for a human element only recently began to be more widely acknowledged. Interactive Evolutionary Computing (IEC), made popular by Karl Sims, effectively solves many high dimension problems, like music composition, involving creative and subjective elements. This work applies several Genetic Algorithm (GA) and Genetic Programming (GP) approaches, inspired by Karl Sims, to algorithmic music composition. The implementation of these IEC algorithms is described and their effectiveness compared