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Scholarly Works, Center for Human-Computer Interaction (CHCI)
Bukvic, Ivica Ico; Matthews, Michael (Georgia Institute of Technology, 2015-07)
In the following paper we present Aegis: a procedural networked soundtrack engine driven by real-time analog signal analysis and pattern recognition. Aegis was originally conceived as part of Drummer Game, a game-performancespectacle hybrid research project focusing on the depiction of a battle portrayed using terracotta soldiers. In it, each of the twelve cohorts—divided into two armies of six—are led by a drummer-performer who issues commands by accurately drumming precomposed rhythmic patterns on an original Chinese war drum. The ensuing spectacle is envisioned to also accommodate large audience participation whose input determines the morale of the two armies. An analog signal analyzer utilizes efficient pattern recognition to decipher the desired action and feed it both into the game and the soundtrack engine. The soundtrack engine then uses this action, as well as messages from the gaming simulation, to determine the most appropriate soundtrack parameters while ensuring minimal repetition and seamless transitions between various clips that account for tempo, meter, and key changes. The ensuing simulation offers a comprehensive system for pattern-driven input, holistic situation assessment, and a soundtrack engine that aims to generate a seamless musical experience without having to resort to cross-fades and other simplistic transitions that tend to disrupt a soundtrack’s continuity.