The aesthetics of deconstruction: neural synthesis of transformation matrices using GANs on multichannel polyphonic MIDI data

Abstract

Deconstruction, a concept that originated from French philosopher Jacques Derrida's post-structuralist theories, has significantly influenced architecture and graphic design. It has evolved into a rhizomatic network of styles and concepts ranging from new architectural geometry to AI. Despite its limited explicit application in music, this paper explores deconstruction within musical aesthetics, especially in the post-1945 serial school. Computer-Aided Design (CAD) methods have become an important part in the deconstructivist architectural design process; similarly, in music, Computer-Aided Composition (CAC) techniques have become important from generative algorithms to AI techniques. In graphic design, such systems (i.e. GANs, VAEs, CNNs, RNNs, Stable Diffusion, Transformers, etc.) have been experimented with. Google's Imagen or OpenAI's DALL-E 2, which automatically generate images from text prompts given by users, use, for example, diffusion models. Also, Google LM is a music equivalent to these. This paper delves into the novel aesthetics brought about by the application of GANs on multichannel polyphonic MIDI data in music, discussing the conceptual grounding of such usage and overcoming the challenges associated with it. Effectively, using our concept of distance matrices rather than, for example, Hidden Markov Models, is more suitable for GAN generation.

KEYWORDS:

• Deconstructivism
• artificial intelligence (AI)
• general adversarial networks (GAN)
• computer-aided composition (CAC)

Acknowledgments

We wish to thank the following for providing permission to reproduce artworks and scores in our paper: Casa Ricordi for the reproduction of Rara Requiem (1969) by Sylvano Bussotti, Faber Music Limited for Ryoanji (1983–1985) by John Cage, Black Angel (1970) by George Crumb and La Terre est Un Homme (1979) by Brian Ferneyhough, Les Amis de Xenakis for Symos (1959) and Pithoprakta (1956) by Iannis Xenakis; as well as, Coop Himmelb(l)au for the reproduction of pictures from the Deep Himmelb(l)au (2020) research project.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 We have drunk some wine in all times (transl. by the author).

2 In all have some drunk times wine We (transl. by the author).