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AI Music Problem: Why Machine Learning Conflicts With Musical Creativity [Minkštas viršelis]

  • Formatas: Paperback / softback, 186 pages, aukštis x plotis: 229x152 mm, weight: 370 g, 12 Illustrations, black and white
  • Išleidimo metai: 17-Jun-2025
  • Leidėjas: Routledge
  • ISBN-10: 1032959754
  • ISBN-13: 9781032959757
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 186 pages, aukštis x plotis: 229x152 mm, weight: 370 g, 12 Illustrations, black and white
  • Išleidimo metai: 17-Jun-2025
  • Leidėjas: Routledge
  • ISBN-10: 1032959754
  • ISBN-13: 9781032959757
Kitos knygos pagal šią temą:

As artificial intelligence has become increasingly sophisticated at producing many forms of media, it continues to be a challenge for AI to reliably and independently write convincing, enjoyable music without human guidance. The AI Music Problem: Why Machine Learning Conflicts With Musical Creativity asks why producing and constructing music is difficult for AI, with an investigation that straddles the technical, the musical, and the aesthetic. Bringing together the perspectives of the humanities and computer science, the author shows how the difficulties that music poses for AI connect to larger questions about music, artistic expression, and the increasing ubiquity of artificial intelligence.

Taking a wide view of the current landscape of machine learning and Large Language Models, The AI Music Problem offers a resource for students, researchers, and the public to understand the broader issues surrounding musical AI on both technical and artistic levels. The author breaks down music theory and computer science concepts with clear and accessible explanations, synthesizing both the technical with more holistic and human-centric analyses. Enabling readers of all backgrounds to understand how contemporary AI models work, and why music is often a mismatch for those processes, this insightful book is relevant to all those engaging with the intersection between AI and musical creativity today.



The AI Music Problem: Why Machine Learning Conflicts With Musical Creativity asks why producing and constructing music is difficult for AI, with an investigation that straddles the technical, the musical, and the aesthetic.

Recenzijos

"White is back with another timely topic, complete with his characteristic attention to rich and relevant context, and to engaging, communicative, and inclusive writing. Inclusive though it is, The AI Music Problem does not pull punches expect to be challenged with a strong argument not only for why AI music currently falls short but (much more interestingly) why he thinks it always will."

Mark Gotham, King's College London

"Chris White provides the definitive guide to one of 21st-century music's most pressing questions. Approaching the topic from a wide variety of angles, The AI Music Problem is both clear and thorough in its exploration of what we should expect as technologies continue to advance, and, perhaps more importantly, what we shouldn't."

Cory Arnold, 12tone YouTube channel

1. The Problems Facing Musical Artificial Intelligence2. History, Engineering, and Motivations Behind Generative Musical AI3. Collecting Examples for Musical Datasets4. Representing Music to Artificial Intelligence5. Musical Structure is Hard to Learn6. Interpreting Musical Artificial Intelligence
Christopher W. White is Associate Professor of Music Theory at the University of Massachusetts Amherst.