Choosers: A Visual Programming Language for Nondeterministic Music Composition by Non-Programmers

Bellingham, Matt (2022). Choosers: A Visual Programming Language for Nondeterministic Music Composition by Non-Programmers. PhD thesis The Open University.



This thesis focuses on the design of Choosers, a prototype algorithmic programming system centred around a new abstraction (of the same name) designed to allow non-programmers access to nondeterministic music composition methods.

Algorithmic composition typically involves structural elements such as indeterminism, parallelism, choice, multi-choice, nesting, weighting, and looping. There are powerful existing tools for manipulating these and other elements of music. However, while these systems give substantial compositional power to musicians who are also skilled programmers, many musicians who lack programming skills find these tools inaccessible and difficult to understand and use. This thesis presents the design and evaluation of a prototype visual programming language designed to allow structural elements of the kind involved in nondeterministic music composition to be readily visualised and manipulated, while making little or no demand on programming ability.

Initially, a Cognitive Dimensions of Notations review of a representative selection of user interfaces for algorithmic composition software was conducted. The review led to a set of findings used to identify candidate design principles which were then tested via a series of design exercises. The findings from these design exercises led to the development of a new abstraction, the Chooser, via a series of iterative design cycles. Once a candidate design had been finalised it was evaluated with participants via two sets of programming walkthroughs, with the findings from each step used to refine the formalism. The final study used Choosers as a design probe through a series of interviews with domain experts in which manipulable compositions were introduced to prompt discussions on potential future implications for music computing education, music production, and music composition.

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