Scribe: Machine Learning, Parafiction, and the Perversion of Practice

Author:

Dyer Mark1ORCID

Affiliation:

1. Mark Dyer, Royal Holloway University of London, Department of Music, Egham Hill, Egham, Surrey, TW20 0EX, U.K. Email: mark.dyer@rhul.ac.uk. Website: www.markdyercomposer.com.

Abstract

Abstract Scribe (2022) is a choral work for three voices. It is a multidisciplinary project that encompasses paleography, machine learning, transcription, and performance. Furthermore, Scribe is a work of parafictional art where fact and fiction overlap, conventional practices of paleography and edition-making are playfully reconfigured, and supposed historical authenticity is employed as a compositional material. This paper describes the creative processes in the making of Scribe before evaluating aspects of the uncanny and material agency. It draws upon autoethnographic analysis before contextualizing this within the psychoanalytical criticism of philosopher Slavoj Žižek.

Publisher

MIT Press

Subject

Computer Science Applications,Music,Engineering (miscellaneous),Visual Arts and Performing Arts

Reference22 articles.

1. “Multimodality and Memory in the Mise en page of Guillaume de Machaut’s Mass,”;Maxwell,2019

2. “Art in the Age of Machine Intelligence,”;Arcas;Arts,2017

3. Margaret Bent , “Old Hall Manuscript,” Grove Music Online (2001): www.oxfordmusiconline.com/grovemusic/view/10.1093/gmo/9781561592630.001.0001/omo-9781561592630-e-0000020296 (accessed 1 November 2022).

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