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  • 标题:Listening without ears: Artificial intelligence in audio mastering:
  • 本地全文:下载
  • 作者:Thomas Birtchnell ; Thomas Birtchnell
  • 期刊名称:Big Data & Society
  • 电子版ISSN:2053-9517
  • 出版年度:2018
  • 卷号:5
  • 期号:2
  • DOI:10.1177/2053951718808553
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:Since the inception of recorded music there has been a need for standards and reliability across sound formats and listening environments. The role of the audio mastering engineer is prestigious and akin to a craft expert combining scientific knowledge, musical learning, manual precision and skill, and an awareness of cultural fashions and creative labour. With the advent of algorithms, big data and machine learning, loosely termed artificial intelligence in this creative sector, there is now the possibility of automating human audio mastering processes and radically disrupting mastering careers. The emergence of dedicated products and services in artificial intelligence-driven audio mastering poses profound questions for the future of the music industry, already having faced significant challenges due to the digitalization of music over the past decades. The research reports on qualitative and ethnographic inquiry with audio mastering engineers on the automation of their expertise and the potential for artificial intelligence to augment or replace aspects of their workflows. Investigating audio mastering engineers' awareness of artificial intelligence, the research probes the importance of criticality in their labour. The research identifies intuitive performance and critical listening as areas where human ingenuity and communication pose problems for simulation. Affective labour disrupts speculation of algorithmic domination by highlighting the pragmatic strategies available for humans to adapt and augment digital technologies.
  • 关键词:Algorithmic cultures; artificial intelligence; audio post-production; criticality; machine learning; music technology
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