Audience Interactivity and the Concert Hall Audience

Audience Interactivity and the Concert Hall Audience Lanier Sammons The second half of the 20"‘ century and the beginning of the 215‘ have witnessed the creation of a largely unanalyzed body of works that harness as a creative force audiences gathered together for a shared musical experience. This dissertation seeks to examine the emergence of these audience-interactive works, offer classification designed to illustrate the range of such works, consider the myriad aesthetic and social concerns that composers of these works must address, and contribute to this oeuvre through the composition of new audience-interactive works. This dissertation explores audience interactive music and its creation 11 through concepts like Christopher Small's musicking" and Nicolas Bourriaud's "relational aesthetics" and situates audience interactivity within work from scholars of play, ethnomusicology, and aesthetics. The dissertation also includes in-depth analysis of audience-interactive pieces composed by Pauline Oliveros, Robert Ashley, ]ason Freeman, Bruce Adolphe, and members of Fluxus. The composition portion of the dissertation consists of five works: a set of event scores calling for audience improvisation, a work for computer-generated sound and images resulting from data produced by audience-directed sensors, a branching musical structure through which a performer navigates based on audience preferences, a system for reading characteristics of an audience as notation, and a piece in which audience members move about the performance space to offer individual musical prompts to performers. This collection of compositions demonstrates both the diversity of iv techniques for achieving audience interactivity and the multitude of purposes for which audience interactivity may be used. Taken as a whole, the dissertation aims to comprehensively consider concert-hall-audience-based audience interactivity through analytical, theoretical, and creative means.

Note: Abstract extracted from PDF file via OCR