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New Directions in Soundscape-based Sound-Art: Hybridising Autoethnography with Computational Analysis

Authors: Barrett Natasha;

New Directions in Soundscape-based Sound-Art: Hybridising Autoethnography with Computational Analysis

Abstract

Real-world sound environments feature throughout sound-art. Fixed media soundscape compositions, electroacoustic music addressing eco-structuralism, site-specific sound installations, performers that use the sound landscape as their stage, and architects and city- planners that design sound-sensitive structures are increasingly common. Despite this intense interest in soundscape-based sound-art, the creative approach developed in the early years of recording generally persists in current practice: that is, a process guided by experiential self-reflection. This approach has served for many decades, yet tends towards a closed loop limited by the ear’s and body’s variable awareness. I propose a practice that hybridises autoethnography with computational analysis to overcome the limitations of experiential personal reflection, without denying the value of the artist as the creative force. In this paper I have chosen to focus on the affordances of spatial sound in outdoor environments framed in a musical perspective. The work draws on the perceptual theories of Gibson and Ingold, and on the possibilities that computational tools such as 3D sound decomposition and music information retrieval have to offer. To illustrate the hybridisation approach, I present non-technical examples from my current experiments. The work is part of the Reconfiguring the Landscape project funded by the Norwegian Artistic Research Council.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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