AI and Music

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2022, held as part of Evo* 2022, in April 2022, co-located with the Evo* 2022 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 6 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP.  The 24 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

This book is intended for researchers interested in using computational methods and tools to engage with music, dance and theatre. The chapters have evolved out of presentations and deliberations at an international workshop entitled Computer Assisted Music and Dramatics: Possibilities and Challenges organized by University of Mumbai in honour of Professor Hari Sahasrabuddhe, a renowned educator and a pioneering computational musicologist (CM) of Indian classical music. The workshop included contributions from CM as well as musicians with a special focus on South Asian arts. The case studies and reflective essays here are based on analyses of genres, practices and theoretical constructs modelled computationally. They offer a balanced and complementary perspective to help innovation in the synthesis of music by extracting information from recorded performances. This material would be of interest to scholars of the sciences and humanities and facilitate exchanges and generation of ideas.

Mathematical Music offers a concise and easily accessible history of how mathematics was used to create music. The story presented in this short, engaging volume ranges from ratios in antiquity to random combinations in the 17th century, 20th-century statistics, and contemporary artificial intelligence. This book provides a fascinating panorama of the gradual mechanization of thought processes involved in the creation of music. How did Baroque authors envision a composition system based on combinatorics? What was it like to create musical algorithms at the beginning of the 20th century, before the computer became a reality? And how does this all explain today's use of artificial intelligence and machine learning in music? In addition to discussing the history and the present state of mathematical music, Braguinski also takes a look at what possibilities the near future of music AI might hold for listeners, musicians, and the society. Grounded in research findings from musicology and the history of technology, and written for the non-specialist general audience, this book helps both student and professional readers to make sense of today's music AI by situating it in a continuous historical context.

This book discusses the principles, methodologies, and challenges of robotic musicianship through an in-depth review of the work conducted at the Georgia Tech Center for Music Technology (GTCMT), where the concept was first developed. Robotic musicianship is a relatively new research field that focuses on the design and development of intelligent music-making machines. The motivation behind the field is to develop robots that not only generate music, but also collaborate with humans by listening and responding in an expressive and creative manner. This combination of human and machine creativity has the potential to surprise and inspire us to play, listen, compose, and think about music in new ways. The book provides an in-depth view of the robotic platforms designed at the GTCMT Robotic Musicianship Group, including the improvisational robotic percussionists Haile and Shimon, the personal robotic companion Shimi, and a number of wearable robots, such as the Robotic Drumming Prosthesis, The Third Drumming Arm, and the Skywalker Piano Hand. The book discusses numerous research studies based on these platforms in the context of five main principles: Listen like a Human, Play Like a Machine, Be Social, Watch and Learn, and Wear It.  

This book critically examines the integration of generative artificial intelligence (Gen AI) in music education, exploring its transformative potential and associated risks. It underscores the necessity for innovative AI pedagogies across music and the arts, offering educators, researchers, and policymakers valuable insights for incorporating Gen AI into teaching while mitigating its hazards. By adopting a balanced critical perspective, the book aims to promote a dynamic, inclusive, and responsible educational approach that is responsive to the rapid advancements in adaptive technology. The book's argumentation is grounded in synthesizing Deweyan pragmatist and Baradian posthumanist philosophical perspectives. These perspectives collectively provide a framework for addressing the deployment of Gen AI in music education within a broader ethical context of global sustainability. The book is also informed by the author's many years as a scholar of music education.