Abstract
ABSTRACTAlgorithmic composition is extended to textual data, demonstrating a novel text setting method. We represent key words of documents through ‘data choralification’, being a polyphonic singing equivalent of word clouds. Using documents about sexual assault, which was the theme of a six-movement choral work, of which the choralification was one movement, frequent words had their word frequencies mapped to audio frequencies in the normal choir vocal range, after removing stop words. Words were allocated to vocal parts and sung simultaneously. The impact of composition decisions is discussed. Automated choralification of data using synthetic voices challenges the current definition of sonification.
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