Debris: Machine learning, archive archaeology, digital audio waste

IF 0.2 3区 艺术学 0 MUSIC
Roberto Alonso Trillo, Marek Poliks
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引用次数: 0

Abstract

This article fragments and processes Debris, a project developed to formalise the creative recycling of digital audio byproducts. Debris began as an open call for electronic compositions that take as their point of departure gigabytes of audio material generated through training and calibrating Demiurge, an audio synthesis platform driven by machine learning. The Debris project led us down rabbitholes of structural analysis: what does it mean to work with digital waste, how is it qualified, and what new relationships and methodologies do this foment? To chart the fluid boundaries of Debris and pin down its underlying conceptualisation of sound, this article introduces a framework ranging from archaeomusicology to intertextuality, from actor-network theory to Deleuzian assemblage, from Adornian constellation to swarm intelligence to platform and network topology. This diversity of approaches traces connective frictions that may allow us to understand, from the perspective of Debris, what working with sound means under the regime of machine intelligence. How has machine intelligence fundamentally altered the already shaky diagram connecting humans, creativity and history? We advise the reader to approach the text as a multisensory experience, listening to Debris while navigating the circuitous theoretical alleys below.
碎片:机器学习、档案考古学、数字音频垃圾
这篇文章的碎片和处理碎片,一个项目开发的形式化创造性回收的数字音频副产品。“碎片”一开始是一个公开征集电子作品的活动,这些电子作品的出发点是通过训练和校准Demiurge(一个由机器学习驱动的音频合成平台)产生的千兆字节音频材料。碎片项目把我们带进了结构分析的兔子洞:处理数字废物意味着什么,它是如何合格的,以及它引发了什么新的关系和方法?为了绘制碎片的流动边界并确定其潜在的声音概念,本文引入了一个框架,从考古音乐学到互文性,从行动者网络理论到德勒兹组合,从阿多尼星座到群体智能,再到平台和网络拓扑。从碎片的角度来看,这种方法的多样性可以让我们理解,在机器智能的统治下,与声音打交道意味着什么。机器智能如何从根本上改变了连接人类、创造力和历史的已经摇摇欲坠的图表?我们建议读者将文本作为一种多感官体验,一边听《碎片》一边浏览下面迂回的理论小巷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.20
自引率
16.70%
发文量
38
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