Mapping the Klangdom Live: Cartographies for Piano with Two Performers and Electronics

Abstract

This is the published version of the paper.This version of the publication may differ from the final published version. Abstract: The use of high-density loudspeaker arrays (HDLAs) has recently experienced rapid growth in a wide variety of technical and aesthetic approaches. Still less explored, however, are applications to interactive music with live acoustic instruments. How can immersive spatialization accompany an instrument already with its own rich spatial diffusion pattern, like the grand piano, in the context of a score-based concert work? Potential models include treating the spatialized electronic sound in analogy to the diffusion pattern of the instrument, with spatial dimensions parametrized as functions of timbral features. Another approach is to map the concert hall as a three-dimensional projection of the instrument's internal physical layout, a kind of virtual sonic microscope. Or, the diffusion of electronic spatial sound can be treated as an independent polyphonic element, complementary to but not dependent upon the instrument's own spatial characteristics. Cartographies (2014), for piano with two performers and electronics, explores each of these models individually and in combination, as well as their technical implementation with the Meyer Sound Matrix3 system of the Südwestrundfunk Experimentalstudio in Freiburg, Germany, and the 43.4-channel Klangdom of the Institut für Musik und Akustik at the Zentrum für Kunst und Media in Karlsruhe, Germany. The process of composing, producing, and performing the work raises intriguing questions, and invaluable hints, for the composition and performance of live interactive works with HDLAs in the future. Permanent repository link

Historical Evolution and Modern Development of Piano Performance - A Visual Analysis Based on Cite space

“…The clustering algorithm used in CiteSpace is the interclass distance algorithm in hierarchical clustering algorithms. One of the most common is the interclass average distance algorithm with the formula shown in (13). Where p, q are two clustering clusters, the determination of the distance between them relies on the average distance between cells i, j:…”

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Feature Extraction and Musical Personality Analysis of Piano Artistic Performances

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