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http://hdl.handle.net/1893/34678
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Avdeeff, Melissa | en_UK |
dc.date.accessioned | 2022-11-17T01:03:29Z | - |
dc.date.available | 2022-11-17T01:03:29Z | - |
dc.date.issued | 2019-12 | en_UK |
dc.identifier.other | 130 | en_UK |
dc.identifier.uri | http://hdl.handle.net/1893/34678 | - |
dc.description.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”. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | MDPI AG | en_UK |
dc.relation | 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 | en_UK |
dc.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. | en_UK |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_UK |
dc.subject | artificial intelligence | en_UK |
dc.subject | popular music | en_UK |
dc.subject | posthuman | en_UK |
dc.subject | creativity | en_UK |
dc.subject | uncanny valley | en_UK |
dc.title | Artificial Intelligence & Popular Music: SKYGGE, Flow Machines, and the Audio Uncanny Valley | en_UK |
dc.type | Journal Article | en_UK |
dc.identifier.doi | 10.3390/arts8040130 | en_UK |
dc.citation.jtitle | Arts | en_UK |
dc.citation.issn | 2076-0752 | en_UK |
dc.citation.volume | 8 | en_UK |
dc.citation.issue | 4 | en_UK |
dc.citation.publicationstatus | Published | en_UK |
dc.citation.peerreviewed | Refereed | en_UK |
dc.type.status | VoR - Version of Record | en_UK |
dc.contributor.funder | Coventry University | en_UK |
dc.author.email | melissa.avdeeff@stir.ac.uk | en_UK |
dc.citation.date | 11/10/2019 | en_UK |
dc.contributor.affiliation | Coventry University | en_UK |
dc.identifier.isi | WOS:000506640300008 | en_UK |
dc.identifier.wtid | 1851368 | en_UK |
dc.date.accepted | 2019-10-08 | en_UK |
dcterms.dateAccepted | 2019-10-08 | en_UK |
dc.date.filedepositdate | 2022-11-14 | en_UK |
dc.subject.tag | Academic discourses | en_UK |
dc.subject.tag | Artificial Intelligence | en_UK |
dc.subject.tag | Audiences | en_UK |
dc.subject.tag | Music Perception | en_UK |
dc.subject.tag | Sociology of Technology | en_UK |
rioxxterms.apc | not charged | en_UK |
rioxxterms.type | Journal Article/Review | en_UK |
rioxxterms.version | VoR | en_UK |
local.rioxx.author | Avdeeff, Melissa| | en_UK |
local.rioxx.project | Project ID unknown|Coventry University|http://dx.doi.org/10.13039/501100001313 | en_UK |
local.rioxx.freetoreaddate | 2022-11-14 | en_UK |
local.rioxx.licence | http://creativecommons.org/licenses/by/4.0/|2022-11-14| | en_UK |
local.rioxx.filename | arts-08-00130-v3.pdf | en_UK |
local.rioxx.filecount | 1 | en_UK |
local.rioxx.source | 2076-0752 | en_UK |
Appears in Collections: | Communications, Media and Culture Journal Articles |
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File | Description | Size | Format | |
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arts-08-00130-v3.pdf | Fulltext - Published Version | 488.43 kB | Adobe PDF | View/Open |
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