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Recalling the Traces of Ancient Fires: Memory and Composed Reinterpretation in Vestigia Flammae for sinfonietta and Agnosco Veteris for orchestra

The musical portion of this dissertation is comprised of my two compositions: Agnosco Veteris, a fifteen-and-a-half-minute work for orchestra, written in 2015 for Robert Spano and the Aspen Philharmonic Orchestra; and its partner and template Vestigia Flammae, a fourteen-minute work for sinfonietta (fifteen musicians) written in 2014 for the Nouvel Ensemble Modern. The written portion of this dissertation is an accompanying essay that provides a conceptual and musical analysis of the partnered pieces. The essay situates the compositions within the context of my recent musical output by specifically focusing on a method I have heartily employed from 2011-16: the reuse of musical/sonic material through repetition, computer-aided manipulation, reorchestration, composed reinterpretation, and self-appropriation. Agnosco Veteris and Vestigia Flammae are partner works that engage with personal musical memories. I explain the desires behind, and the process of, transforming one piece into another. A section of the essay places this concept in the historical context of other composers who employ appropriation of material and methods of reorchestration to generate new works. I discuss my compositional process and style as an alloy of my musical genetic makeup – a mixing ground of my experience as a performer of the classical canon in dialogue with my affinity towards minimalism, modernism, romanticism, spectralism, Slavic folk and liturgical musics, electronic music, and popular music production techniques. The latter portion of the essay provides a theoretical analysis of the two pieces in terms of poetic genesis, form, motivic material, harmonic structure, orchestration, texture, and rhythmic development.

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8348R2C
Date January 2017
CreatorsYoung, Nina C.
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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