AI-terity 2.0: An Autonomous NIME Featuring GANSpaceSynth Deep Learning Model

Koray Tahiroğlu, Miranda Kastemaa, Oskar Koli

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

In this paper we present the recent developments in the AI-terity instrument. AI-terity is a deformable, non-rigid musical instrument that comprises a particular artificial intelligence (AI) method for generating audio samples for real-time audio synthesis. As an improvement, we developed the control interface structure with additional sensor hardware. In addition, we implemented a new hybrid deep learning architecture, GANSpaceSynth, in which we applied the GANSpace method on the GANSynth model. Following the deep learning model improvement, we developed new autonomous features for the instrument that aim at keeping the musician in an active and uncertain state of exploration. Through these new features, the instrument enables more accurate control on GAN latent space. Further, we intend to investigate the current developments through a musical composition that idiomatically reflects the new autonomous features of the AI-terity instrument. We argue that the present technology of AI is suitable for enabling alternative autonomous features in audio domain for the creative practices of musicians.
Original languageEnglish
Title of host publicationProceedings of the International Conference on New Interfaces for Musical Expression
PublisherInternational Conference on New Interfaces for Musical Expression
Volume2021
DOIs
Publication statusPublished - 15 Jun 2021
MoE publication typeA4 Article in a conference publication
EventInternational Conference on New Interfaces for Musical Expression - Shanghai, China
Duration: 15 Jun 202118 Jun 2021
http://nime2021.org/

Publication series

Name
ISSN (Electronic)2220-4806

Conference

ConferenceInternational Conference on New Interfaces for Musical Expression
Abbreviated titleNIME
CountryChina
CityShanghai
Period15/06/202118/06/2021
Internet address

Keywords

  • Artificial Intelligence (AI)
  • new interfaces for musical expression
  • Digital musical instruments
  • Deep Learning
  • GAN
  • GANSpaceSynth
  • SOPI
  • NIME

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