Algorithmically Generating Musical Complexity Based on Textual Complexity; A Case Study

Daniel Field, Griffith University Part of CW18

This presentation gives the audience a quick tour through the development process for the ‘Word Score Sonifier’, a Python script that takes English text as input and provides a four-part vocal score (soprano, alto, tenor, bass) as output in MusicXML. The Word Score Sonifier was rapidly developed for the 2018 National Science Week ‘Textual Data Sonification and Algorithmic Composition Competition’, where it won the open category.

The focus of the presentation will be on the musical and creative choices embedded in the algorithm, both express and implied. The presenter will trace the intent to create a flexible composition algorithm capable of producing outputs spanning a stylistic range; how that intent was incorporated into the algorithm by means of flexible procedures, and how the notion of textual complexity was used as a control parameter and mapped to musical complexity using common-practice tonality and major modal theory as a reference. The audience will hear examples of compositions and will be able to judge for themselves the extent to which the intent may or may not have been fully realised.

Daniel Field is an engineer by vocation and a musician by avocation. He is currently combining his skills, interests and passions by studying a research Masters on the topic of algorithmic improvisation, part time, at Queensland Conservatorium Griffith University.