Please use this identifier to cite or link to this item:
http://hdl.handle.net/1893/34678
Appears in Collections: | Communications, Media and Culture Journal Articles |
Peer Review Status: | Refereed |
Title: | Artificial Intelligence & Popular Music: SKYGGE, Flow Machines, and the Audio Uncanny Valley |
Author(s): | Avdeeff, Melissa |
Contact Email: | melissa.avdeeff@stir.ac.uk |
Keywords: | artificial intelligence popular music posthuman creativity uncanny valley |
Issue Date: | Dec-2019 |
Date Deposited: | 14-Nov-2022 |
Citation: | Avdeeff M (2019) Artificial Intelligence & Popular Music: SKYGGE, Flow Machines, and the Audio Uncanny Valley. <i>Arts</i>, 8 (4), Art. No.: 130. https://doi.org/10.3390/arts8040130 |
Abstract: | This article presents an overview of the first AI-human collaborated album, Hello World, by SKYGGE, which utilizes Sony’s Flow Machines technologies. This case study is situated within a review of current and emerging uses of AI in popular music production, and connects those uses with myths and fears that have circulated in discourses concerning the use of AI in general, and how these fears connect to the idea of an audio uncanny valley. By proposing the concept of an audio uncanny valley in relation to AIPM (artificial intelligence popular music), this article offers a lens through which to examine the more novel and unusual melodies and harmonization made possible through AI music generation, and questions how this content relates to wider speculations about posthumanism, sincerity, and authenticity in both popular music, and broader assumptions of anthropocentric creativity. In its documentation of the emergence of a new era of popular music, the AI era, this article surveys: (1) The current landscape of artificial intelligence popular music focusing on the use of Markov models for generative purposes; (2) posthumanist creativity and the potential for an audio uncanny valley; and (3) issues of perceived authenticity in the technologically mediated “voice”. |
DOI Link: | 10.3390/arts8040130 |
Rights: | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Licence URL(s): | http://creativecommons.org/licenses/by/4.0/ |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
arts-08-00130-v3.pdf | Fulltext - Published Version | 488.43 kB | Adobe PDF | View/Open |
This item is protected by original copyright |
A file in this item is licensed under a Creative Commons License
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/
If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.