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Soundwalking Deep Latent Spaces

Authors: Scurto, Hugo; Postel, Ludmila;

Soundwalking Deep Latent Spaces

Abstract

This paper relates an early art-research collaboration between two practitioners in machine learning and virtual worlds toward new embodied musical experiences of Artificial Intelligence (AI). Instead of a digital music instrument or a music-generating agent, we propose to craft a soundwalk experience where a human person moves through a three-dimensional virtual world to explore a latent sound space generated by deep learning. We report on the diffractive prototyping and iterative crafting of three such soundwalks through/out deep latent spaces, using nn~ and New Atlantis as computational platforms for AI audio processing and virtual world experimentation. We share critical perspectives emerging from our latent soundwalking practice, with the hope that they contribute to ongoing community-wide reflections toward new AI for musical expression.

Keywords

[SHS.MUSIQ] Humanities and Social Sciences/Musicology and performing arts, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Soundwalk, Artificial Intelligence, Virtual World, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], Generative Deep Learning

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selected citations
These citations are derived from selected sources.
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!
0
Average
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