This volume presents the most up-to-date collection of neural network models of music and creativity gathered together in one place. Chapters by leaders in the field cover new connectionist models of pitch perception, tonality, musical streaming, sequential and hierarchical melodic structure, composition, harmonization, rhythmic analysis, sound generation, and creative evolution. The collection combines journal papers on connectionist modeling, cognitive science, and music perception with new papers solicited for this volume. It also contains an extensive bibliography of related work. Contributors Shumeet Baluja, M.I. Bellgard, Michael A. Casey, Garrison W. Cottrell, Peter Desain, Robert O. Gjerdingen, Mike Greenhough, Niall Griffith, Stephen Grossberg, Henkjan Honing, Todd Jochem, Bruce F. Katz, John F. Kolen, Edward W. Large, Michael C. Mozer, Michael P.A. Page, Caroline Palmer, Jordan B. Pollack, Dean Pomerleau, Stephen W. Smoliar, Ian Taylor, Peter M. Todd, C.P. Tsang, Gregory M. Werner

The impact of digital technology on the musical economy has been profound. From its production, reproduction, distribution, and consumption, the advent of MP3 and the use of the Internet as a medium of distribution has brought about a significant transformation in the way that music is made, how it is purchased and listened to, and, significantly, how the musical economy itself is able to reproduce itself. In the late 1990s the obscure practice of 'ripping' tracks from CDs through the use of compression programmes was transformed from the illegal hobby of a few thousand computer specialists to a practice available to millions of people worldwide through the development of peer-to-peer computer networks. This continues to have important implications for the viability of the musical economy. At the same time, the production of music has become more accessible and the role of key gatekeepers in the industry—such as record companies and recording studios— has been undermined, whilst the increased accessibility of music at reduced cost via the Internet has revalorised live performance, and now generates revenues higher than recorded music. The early 21st century has provided an extraordinary case study of an industry in flux, and one that throws light on the relationship between culture and economy, between passion and calculation. This book provides a theoretically grounded account of the implications of digital technology on the musical economy, and develops the concept of the musical network to understand the transformation of this economy over space and through time.

Social networks are critical for the creation and consumption of music. This edited collection, Social Networks and Music Worlds, introduces students and scholars of music in society to the core concepts and tools of social network analysis. The collection showcases the use of these tools by sociologists, historians and musicologists, examining a variety of distinct 'music worlds', including post-punk, jazz, rap, folk, classical music, Ladyfest and the world of 'open mic' performances, on a number of different scales (local, national and international). In addition to their overarching Introduction, the editors offer a very clear and detailed introduction to the methodology of social network analysis for the uninitiated. The collection builds upon insights from canonic texts in the sociology of music, with the crucial innovation of examining musical network interaction via formal methods. With network analysis in the arts and humanities at an emergent stage, Social Networks and Music Worlds highlights its possibilities for non-scientists. Contributions hail from leading and emerging scholars who present social network graphs and data to represent different music worlds, locating individuals, resources and styles within them. The collection sits at the nexus of sociological, musicological and cultural studies traditions. Its range should ensure a large scholarly readership.

Networking the Russian Diaspora is a fascinating and timely study of interwar Shanghai. Aside from the vacated Orthodox Church in the former French Concession where most Russian émigrés resided, Shanghai today displays few signs of the bustling settlement of those years. Russian musicians established the first opera company in China, as well as choirs, bands, and ensembles, to play for their own and other communities. Russian musicians were the core of Shanghai’s lauded Municipal Orchestra and taught at China’s first conservatory. Two Russian émigré composers in particular—Alexander Tcherepnin and Aaron Avshalomov—experimented with incorporating Chinese elements into their compositions as harbingers of intercultural music that has become a well-recognized trend in composition since the late twentieth century. The Russian musical scene in Shanghai was the embodiment of musical cosmopolitanism, anticipating the hybrid nature of twenty-first-century music arising from cultural contacts through migration, globalization, and technological advancement. As a pioneering study of the Russian community, Networking the Russian Diaspora examines its musical activities and influence in Shanghai. While the focus of the book is on music, it also gives insight into the social dynamics between Russians and other Europeans on the one hand, and with the Chinese on the other. The volume, coauthored by Chinese music specialists, makes a significant contribution to studies of diaspora, cultural identity, and migration by casting light on a little-studied area of Sino-Russian cultural relations and Russian influence in modern China. The discoveries stretch the boundaries of music studies by addressing the relational aspects of Western music: how it has articulated national and cultural identities but also served to connect people of different origins and cultural backgrounds.

Innovation in Music: Technology and Creativity is a groundbreaking collection bringing together contributions from instructors, researchers, and professionals. Split into two sections, covering composition and performance, and technology and innovation, this volume offers truly international perspectives on ever-evolving practices. Including chapters on audience interaction, dynamic music methods, AI, and live electronic performances, this is recommended reading for professionals, students, and researchers looking for global insights into the fields of music production, music business, and music technology.

Previously, artificial neural networks have been used to capture only the informal properties of music. However, cognitive scientist Michael Dawson found that by training artificial neural networks to make basic judgments concerning tonal music, such as identifying the tonic of a scale or the quality of a musical chord, the networks revealed formal musical properties that differ dramatically from those typically presented in music theory. For example, where Western music theory identifies twelve distinct notes or pitch-classes, trained artificial neural networks treat notes as if they belong to only three or four pitch-classes, a wildly different interpretation of the components of tonal music. Intended to introduce readers to the use of artificial neural networks in the study of music, this volume contains numerous case studies and research findings that address problems related to identifying scales, keys, classifying musical chords, and learning jazz chord progressions. A detailed analysis of the internal structure of trained networks could yield important contributions to the field of music cognition.