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dc.contributor.authorBellingham, Matt
dc.contributor.authorHolland, Simon
dc.contributor.authorMulholland, Paul
dc.date.accessioned2020-09-02T13:09:53Z
dc.date.available2020-09-02T13:09:53Z
dc.date.issued2019-08-29
dc.identifier.citationBellingham, M., Holland, S. and Mulholland, P. (2019) Toward meaningful algorithmic music-making for non-programmers, PPIG 2019, 30th Annual Workshop, 28th-30th August 2019, Newcastle University, UKen
dc.identifier.urihttp://hdl.handle.net/2436/623571
dc.descriptionThis is an accepted manuscript of an article published by PPIG in PPIG 2019, 30th Annual Workshop, 28th-30th August 2019. The accepted version of the publication may differ from the final published version.en
dc.description.abstractAlgorithmic composition typically involves manipulating structural elements such as indeterminism, parallelism, choice, multi-choice, recursion, weighting, sequencing, timing, and looping. There exist powerful tools for these purposes, however, many musicians who are not expert programmers find such tools inaccessible and difficult to understand and use. By analysing a representative selection of user interfaces for algorithmic composition, through the use of the Cognitive Dimensions of Notations (CDN) and other analytical tools, we identified candidate design principles, and applied these principles to create and implement a new visual formalism, programming abstraction and execution model. The resulting visual programming language, Choosers, is designed to allow ready visualisation and manipulation of structural elements of the kind involved in algorithmic music composition, while making minimal demand on programming ability. Programming walkthroughs with novice users were used iteratively to refine and validate diverse aspects of the design. Currently, workshops with musical experts and teachers are being conducted to explore the value of the language for varied pragmatic purposes by expressing, manipulating and reflecting on diverse musical examples.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherPsychology of Programming Interest Group (PPIG)en
dc.relation.urlhttps://www.ppig.org/workshops/2019-annual-workshop/programme/en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleToward meaningful algorithmic music-making for non-programmersen
dc.typeConference contributionen
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW02092020MBen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2020-09-02en
refterms.dateFCD2020-09-02T13:09:25Z
refterms.versionFCDAM
refterms.dateFOA2020-09-02T13:09:54Z


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International