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ZENODO
Conference object . 2018
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Conference object . 2018
License: CC BY
Data sources: Datacite
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all the noises hijacking listening machines for performative research

Authors: John Bowers; Owen Green;

all the noises hijacking listening machines for performative research

Abstract

Research into machine listening has intensified in recent years creating a variety of techniques for recognising musical features suitable, for example, in musicological analysis or commercial application in song recognition. Within NIME, several projects exist seeking to make these techniques useful in real-time music making. However, we debate whether the functionally-oriented approaches inherited from engineering domains that much machine listening research manifests is fully suited to the exploratory, divergent, boundary-stretching, uncertainty-seeking, playful and irreverent orientations of many artists. To explore this, we engaged in a concerted collaborative design exercise in which many different listening algorithms were implemented and presented with input which challenged their customary range of application and the implicit norms of musicality which research can take for granted. An immersive 3D spatialised multichannel environment was created in which the algorithms could be explored in a hybrid installation/performance/lecture form of research presentation. The paper closes with reflections on the creative value of 'hijacking' formal approaches into deviant contexts, the typically undocumented practical know-how required to make algorithms work, the productivity of a playfully irreverent relationship between engineering and artistic approaches to NIME, and a sketch of a sonocybernetic aesthetics for our work.

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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).
BIP!Citations provided by BIP!
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.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green