Product details
- ISBN 9781032877426
- Weight: 453g
- Dimensions: 156 x 234mm
- Publication Date: 16 Jul 2026
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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Making Machine Musicians: AI for Live Musical Performance explores the integration of artificial intelligence (AI) technologies into live music performances.
Offering a comprehensive guide to developing “machine musicians” capable of interactive improvisation and real-time collaboration with human performers, this book introduces readers to cutting-edge trends in live musical AI. Chapters combine theoretical discussions, practical tutorials, and hands-on projects, providing step-by-step instructions for building autonomous music systems, experimenting with interactive AI tools, and exploring creative applications of AI in live performance. Accompanying software and tutorials ensure accessibility for musicians of all levels, fostering both technical fluency and artistic innovation. Whether used as a textbook, a self-study guide, or a practical manual; it equips readers with the knowledge and tools to explore the emerging field of musical AI and its potential to transform the way we create and experience music.
This book will appeal to music technology professionals, educators, and novice musicians alike, this book serves as a valuable resource for anyone interested in the intersection of AI and live music.
Jason Palamara is Assistant Professor of Music Technology at Indiana University, Indianapolis, USA. He specialises in developing AI-enabled performance technologies for music. He directs the Indianapolis-based Machine Musician Lab that pursues multiple AI music and performance initiatives. He maintained a long-term creative partnership with the late percussionist-composer and technologist Scott Deal, with whom he developed the interactive AVATAR software. AVATAR is an autonomous music system that uses machine learning to play along with live improvisation. He is also the founder/director of IU’s 30+ member DISEnsemble (Diverse Instrument Symphonic Ensemble), which counts an autonomous digital performer named the Emergent Musical Hologram (EMH) among its performers.
