March 24, 2025
Updated July 15, 2025
14 minute read
An Introduction to Shikaki: Navigating the World of AI-Powered Music Composition
nl0061|
Find a path to becoming a Shikaki. Learn more at:
OpenCourser.com/topic/nl0061/shikak
Reading list
We've selected 23 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Shikaki.
Comprehensive and foundational text in the field of computer music, covering a vast range of topics including algorithmic composition and synthesis techniques. It provides essential historical context and technical details necessary for a deep understanding of how computers have been used to create music, serving as a valuable reference for both students and professionals. While published some time ago, its principles remain highly relevant.
Focusing on the deep learning techniques behind generative AI, this book provides practical insights into building models that can create music, text, and images. It's highly relevant for understanding the current state of AI music generation using neural networks and generative models. is particularly useful for those with a programming background looking to implement generative music systems.
Focuses specifically on deep learning techniques applied to music generation. It delves into various models and architectures used for creating music with AI. It's an important resource for those wanting to understand the state-of-the-art technical methods in this specific area.
Delves into various algorithmic approaches used for music composition, offering a systematic overview of different paradigms. It's essential for gaining a deeper understanding of the computational techniques that underpin much of AI music generation. The book provides both theoretical background and musical applications, making it a valuable resource for those wanting to explore the technical side.
This practical guide focuses on using Google's Magenta library for music generation, providing a hands-on approach to creating music with AI. It's an excellent resource for those who want to implement generative music systems using a popular toolset. It's particularly useful for students and professionals with programming skills.
Providing a thorough historical overview of electronic and computer music, this book is crucial for understanding the lineage of AI music generation. It traces the evolution of the field from its origins to more recent developments, offering context for the emergence of AI in music creation. is excellent for gaining broad historical knowledge and is often used as a reference in academic settings.
Explores the use of computers as generative tools in music composition, introducing various techniques from algorithmic approaches to neural computation. It provides a good overview of different methods for computer-assisted music creation. It valuable resource for students and researchers interested in the technical and creative aspects.
A comprehensive guide to generative AI in music creation, covering fundamental concepts and applications. is aimed at providing readers with the knowledge to utilize AI in their music creative process. It's a contemporary resource for understanding practical aspects of generative music.
While not solely focused on generation, this book provides fundamental knowledge of music processing, analysis, and related algorithms crucial for developing AI music systems. It covers topics like audio features, representations, and algorithms that are prerequisites for many generative techniques. This strong resource for building a solid technical foundation.
A practical guide for musicians and music professionals, this book explores how AI can be used as a creative tool in music generation, production, and promotion. It offers hands-on advice and covers current AI platforms. is excellent for those looking for practical applications of AI in their music workflow.
This edited volume examines the impact of AI on various aspects of the music industry, from production workflows to digital platforms and professional practices. It offers a contemporary perspective on the real-world implications of AI in music. is highly relevant for understanding the current and future landscape of the music business.
Explores the challenges and limitations of AI in creating music, offering a critical perspective on the intersection of machine learning and musical creativity. It delves into the technical, musical, and aesthetic difficulties AI faces. This valuable read for a nuanced understanding of the current state and future potential of AI music.
Examines the broader ecosystem surrounding AI and music, including its impact on the industry, artists, and listeners. It provides a contemporary view of how AI is transforming the creation, distribution, and consumption of music. It's a good resource for understanding the current landscape and future trends.
Examines the broader landscape of AI creativity across various art forms, including music. It provides a cultural and philosophical context for understanding the role of AI in creative processes. While not a technical deep dive, it's a must-read for considering the implications and potential of AI in music from an artistic perspective.
Provides a contemporary analysis of how AI is transforming various creative sectors, including music. It discusses how AI technologies are reshaping creative workflows and generating new opportunities and challenges. It's a relevant read for understanding the broader impact of AI on creative fields today.
Provides a historical perspective on the relationship between mathematics and music, leading up to the use of AI in music creation. It helps contextualize current AI music techniques within a long history of formalizing music. It's a valuable read for understanding the theoretical underpinnings and historical trajectory.
This collection of readings provides a broad overview of key topics in the intersection of music and artificial intelligence. It includes contributions on various approaches and applications, offering a good starting point for exploring different areas within the field. It can serve as a valuable supplementary text.
This guide focuses on algorithmic composition using the Nyquist programming language. It provides a practical approach to generating music through code, illustrating fundamental concepts of algorithmic composition. It's a good resource for those who want to learn by doing and explore a specific historical and still relevant system.
Offers a beginner-friendly introduction to the world of AI-generated music. It covers essential concepts in an accessible manner, making it suitable for those new to the topic. It's a good starting point for gaining a broad understanding without requiring extensive technical background.
An introduction to algorithmic music composition using the Lisp programming language and the Common Music environment. provides a theoretical and practical foundation in algorithmic composition. While the specific tools might be less common now, the underlying concepts are highly relevant for understanding generative music processes.
Explores the cognitive and psychological processes involved in music creation, including composition and improvisation. While not strictly about AI, it provides valuable insights into the human side of generative processes in music, which can inform the development and understanding of AI music systems.
While broader than just music, this book explores the transformative role of generative AI in educational contexts, which is relevant as AI music creation tools become more accessible. It discusses applications and ethical considerations of generative AI, providing a valuable perspective on its use in learning environments related to music technology.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/nl0061/shikak
Save
