The AI Music Problem
Why Machine Learning Conflicts With Musical Creativity
Seiten
2025
Routledge (Verlag)
978-1-032-95976-4 (ISBN)
Routledge (Verlag)
978-1-032-95976-4 (ISBN)
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.
Music poses unique and complex challenges for artificial intelligence, even as 21st-century AI grows ever more adept at generating compelling content. The AI Music Problem: Why Machine Learning Conflicts With Musical Creativity probes the challenges behind AI-generated music, 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 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 book is relevant to all those engaging with the intersection between AI and musical creativity today.
Music poses unique and complex challenges for artificial intelligence, even as 21st-century AI grows ever more adept at generating compelling content. The AI Music Problem: Why Machine Learning Conflicts With Musical Creativity probes the challenges behind AI-generated music, 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 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 book is relevant to all those engaging with the intersection between AI and musical creativity today.
Christopher W. White is Associate Professor of Music Theory at the University of Massachusetts Amherst.
1. The Problems Facing Musical Artificial Intelligence
2. History, Engineering, and Motivations Behind Generative Musical AI
3. Collecting Examples for Musical Datasets
4. Representing Music to an Artificial Intelligence
5. Musical Structure is Hard to Learn
6. Interpreting Musical Artificial Intelligence
| Erscheinungsdatum | 24.04.2025 |
|---|---|
| Zusatzinfo | 12 Line drawings, black and white; 13 Halftones, black and white; 25 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 152 x 229 mm |
| Gewicht | 530 g |
| Themenwelt | Kunst / Musik / Theater ► Musik ► Musiktheorie / Musiklehre |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-032-95976-2 / 1032959762 |
| ISBN-13 | 978-1-032-95976-4 / 9781032959764 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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