Choosers: designing a highly expressive algorithmic music composition system for non-programmers

We present an algorithmic composition system designed to be accessible to those with minimal programming skills and little musical training, while at the same time allowing the manipulation of detailed musical structures more rapidly and more fluidly than would normally be possible for such a user group. These requirements led us to devise non- standard programming abstractions as the basis for a novel graphical music programming language in which a single basic element permits indeterminism, parallelism, choice, multi-choice, recursion, weighting and looping. The system has general musical expressivity, but for simplicity here we focus on manipulating samples. The musical abstractions behind the system have been implemented as a set of SuperCollider classes to enable end-user testing of the graphical programming language via a Wizard of Oz prototyping methodology. The system is currently being tested with undergraduate Music Technology students who are typically neither programmers, nor traditional musicians

Algorithms as scores: coding live music

The author discusses live coding as a new path in the evolution of the musical score. Live-coding practice accentu- ates the score, and whilst it is the perfect vehicle for the performance of algorithmic music it also transforms the compositional process itself into a live event. As a continuation of 20th-century artistic developments of the musical score, live-coding systems often embrace graphical elements and language syntaxes foreign to standard programming languages. The author presents live coding as a highly technologized artistic practice, shedding light on how non-linearity, play and generativity will become prominent in future creative media productions

Automatic Music Composition using Answer Set Programming

Music composition used to be a pen and paper activity. These these days music is often composed with the aid of computer software, even to the point where the computer compose parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named ANTON, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes ANTON unique in the growing area of algorithmic composition. With near real-time composition, ANTON reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, ANTON provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems. This paper has been accepted for publication in Theory and Practice of Logic Programming (TPLP).Comment: 31 pages, 10 figures. Extended version of our ICLP2008 paper. Formatted following TPLP guideline

Choosers: The design and evaluation of a visual algorithmic music composition language for non-programmers

Algorithmic music composition involves specifying music in such a way that it is non-deterministic on playback, leading to music which has the potential to be different each time it is played. Current systems for algorithmic music composition typically require the user to have considerable programming skill and may require formal knowledge of music. However, much of the potential user population are music producers and musicians (some professional, but many amateur) with little or no programming experience and few formal musical skills. To investigate how this gap between tools and potential users might be better bridged we designed Choosers, a prototype algorithmic programming system centred around a new abstraction (of the same name) designed to allow non-programmers access to algorithmic music composition methods. Choosers provides a graphical notation that allows structural elements of key importance in algorithmic composition (such as sequencing, choice, multi-choice, weighting, looping and nesting) to be foregrounded in the notation in a way that is accessible to non-programmers. In order to test design assumptions a Wizard of Oz study was conducted in which seven pairs of undergraduate Music Technology students used Choosers to carry out a range of rudimentary algorithmic composition tasks. Feedback was gathered using the Programming Walkthrough method. All users were familiar with Digital Audio Workstations, and as a result they came with some relevant understanding, but also with some expectations that were not appropriate for algorithmic music work. Users were able to successfully make use of the mechanisms for choice, multi-choice, looping, and weighting after a brief training period. The ‘stop’ behaviour was not so easily understood and required additional input before users fully grasped it. Some users wanted an easier way to override algorithmic choices. These findings have been used to further refine the design of Choosers

Designing a Highly Expressive Algorithmic Music Composition System for Non-Programmers

Algorithmic composition systems allow for the partial or total automation of music composition by formal, computational means. Typical algorithmic composition systems generate nondeterministic music, meaning that multiple musical outcomes can result from the same algorithm - consequently the output is generally different each time the algorithm runs

Teaching rule‐based algorithmic composition: the PWGL library cluster rules

This paper presents software suitable for undergraduate students to implement computer programs that compose music. The software offers a low floor (students easily get started) but also a high ceiling (complex compositional theories can be modelled). Our students are particularly interested in tonal music: such aesthetic preferences are supported, without stylistically restricting users of the software. We use a rule‐based approach (constraint programming) to allow for great flexibility. Our software Cluster Rules implements a collection of compositional rules on rhythm, harmony, melody, and counterpoint for the new music constraint system Cluster Engine by Örjan Sandred. The software offers a low floor by observing several guidelines. The programming environment uses visual programming (Cluster Rules and Cluster Engine extend the algorithmic composition system PWGL). Further, music theory definitions follow a template, so students can learn from examples how to create their own definitions. Finally, students are offered a collection of predefined rules, which they can freely combine in their own definitions. Music Technology students, including students without any prior computer programming experience, have successfully used the software. Students used the musical results of their computer programs to create original compositions. The software is also interesting for postgraduate students, composers and researchers. Complex polyphonic constraint problems are supported (high ceiling). Users can freely define their own rules and combine them with predefined rules. Also, Cluster Engine’s efficient search algorithm makes advanced problems solvable in practice

A Simple Method to Produce Algorithmic MIDI Music based on Randomness, Simple Probabilities and Multi-Threading

This paper introduces a simple method for producing multichannel MIDI music that is based on randomness and simple probabilities. One distinctive feature of the method is that it produces and sends in parallel to the sound card more than one unsynchronized channels by exploiting the multi-threading capabilities of general purpose programming languages. As consequence the derived sound offers a quite ``full" and ``unpredictable" acoustic experience to the listener. Subsequently the paper reports the results of an evaluation with users. The results were very surprising: the majority of users responded that they could tolerate this music in various occasions.Comment: 7 pages, 5 figure