Conformity, deformity and reformity

In any given field of artistic practice, practitioners position themselves—or find themselves positioned—according to interests and allegiances with specific movements, genres, and traditions. Selecting particular frameworks through which to approach the development of new ideas, patterns and expressions, balance is invariably maintained between the desire to contribute towards and connect with a particular set of domain conventions, whilst at the same time developing distinction and recognition as a creative individual. Creativity through the constraints of artistic domain, discipline and style provides a basis for consideration of notions of originality in the context of activity primarily associated with reconfiguration, manipulation and reorganisation of existing elements and ideas. Drawing from postmodern and post-structuralist perspectives in the analysis of modern hybrid art forms and the emergence of virtual creative environments, the transition from traditional artistic practice and notions of craft and creation, to creative spaces in which elements are manipulated, mutated, combined and distorted with often frivolous or subversive intent are considered. This paper presents an educational and musically focused perspective of the relationship between the individual and domain-based creative practice. Drawing primarily from musical and audio-visual examples with particular interest in creative disruption of pre-existing elements, creative strategies of appropriation and recycling are explored in the context of music composition and production. Conclusions focus on the interpretation of creativity as essentially a process of recombination and manipulation and highlight how the relationship between artist and field of practice creates unique creative spaces through which new ideas emerge

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

Bach in a Box - Real-Time Harmony

We describe a system for learning J. S. Bach's rules of musical harmony. These rules are learned from examples and are expressed as rule-based neural networks. The rules are then applied in real-time to generate new accompanying harmony for a live performer. Real-time functionality imposes constraints on the learning and harmonizing processes, including limitations on the types of information the system can use as input and the amount of processing the system can perform. We demonstrate algorithms for generating and refining musical rules from examples which meet these constraints. We describe a method for including a priori knowledge into the rules which yields significant performance gains. We then describe techniques for applying these rules to generate new music in real-time. We conclude the paper with an analysis of experimental results

AI Methods in Algorithmic Composition: A Comprehensive Survey

Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.This study was partially supported by a grant for the MELOMICS project (IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for the CAUCE project (TSI-090302-2011-8) from the Spanish Ministerio de Industria, Turismo y Comercio. The first author was supported by a grant for the GENEX project (P09-TIC- 5123) from the Consejería de Innovación y Ciencia de Andalucía

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/