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The Digital Da Vinci book series opens with the interviews of music mogul Quincy Jones, MP3 inventor Karlheinz Brandenburg, Tommy Boy founder Tom Silverman and entertainment attorney Jay L. Cooper. A strong supporter of science, technology, engineering and mathematics programs in schools, The Black Eyed Peas founding member will.i.am announced in July 2013 his plan to study computer science. Leonardo da Vinci, the epitome of a Renaissance man, was an Italian polymath at the turn of the 16th century. Since the Industrial Revolution in the 18th century, the division of labor has brought forth specialization in the workforce and university curriculums. The endangered species of polymaths is facing extinction. Computer science has come to the rescue by enabling practitioners to accomplish more than ever in the field of music. In this book, Newton Lee recounts his journey in executive producing a Billboard-charting song like managing agile software development; M. Nyssim Lefford expounds producing and its effect on vocal recordings; Dennis Reidsma, Mustafa Radha and Anton Nijholt survey the field of mediated musical interaction and musical expression; Isaac Schankler, Elaine Chew and Alexandre François describe improvising with digital auto-scaffolding; Shlomo Dubnov and Greg Surges explain the use of musical algorithms in machine listening and composition; Juan Pablo Bello discusses machine listening of music; Stephen and Tim Barrass make smart things growl, purr and sing; Raffaella Folgieri, Mattia Bergomi and Simone Castellani examine EEG-based brain-computer interface for emotional involvement in games through music and last but not least, Kai Ton Chau concludes the book with computer and music pedagogy. Digital Da Vinci: Computers in Music is dedicated to polymathic education and interdisciplinary studies in the digital age empowered by computer science. Educators and researchers ought to encourage the new generation of scholars to become as well rounded as a Renaissance man or woman.
Inside Computer Music is an investigation of how new technological developments have influenced the creative possibilities of composers of computer music in the last 50 years. This book combines detailed research into the development of computer music techniques with thorough studies of ninecase studies analysing key works in the musical and technical development of computer music. The text is linked to demonstration videos of the techniques used and software which offers readers the opportunity to try out emulations of the software used by the composers for themselves and view videointerviews with the composers and others involved in the production of the musical works. The software also presents musical analyses of each of the nine case studies using software and video alongside text to enable readers to engage with the musical structure aurally and interactively.
At the conference «Musicology 1966-2000: A Practical Program, » on May 26, 1966, Jan LaRue speculated «that computer analysis will become one of the most important directions in musicology for the next generation...» Having passed the year 2000, we have to realize that LaRue's prediction did not come true: neither for computer-assisted music analysis, nor for computer-applications in music research in general. This volume is intended to initiate a more critical discussion of computer-applications in music research and to present concepts, methods, and results of newest research in this area.
The first of its kind, this is book consists of twenty-one essays describing the many different uses of the digital computer in the field of music. Musicologists will find that various historical periods-from medieval to contemporary-are represented, and examples of computer analysis of ethnic music are considered. Edmund A. Bowles contributes an entertaining historical survey of music research and the computer. Lejaren Hill here discusses computer composition, both in this country and in Europe, and gives a bibliography of composers and their works. A. James Gabura's essay describes experiments in analyzing and identifying the keyboard styles of Haydn, Mozart, and Beethoven. There is also a section of particular interest to music librarians.
This book presents a world-class collection of Brain-Computer Music Interfacing (BCMI) tools. The text focuses on how these tools enable the extraction of meaningful control information from brain signals, and discusses how to design effective generative music techniques that respond to this information. Features: reviews important techniques for hands-free interaction with computers, including event-related potentials with P300 waves; explores questions of semiotic brain-computer interfacing (BCI), and the use of machine learning to dig into relationships among music and emotions; offers tutorials on signal extraction, brain electric fields, passive BCI, and applications for genetic algorithms, along with historical surveys; describes how BCMI research advocates the importance of better scientific understanding of the brain for its potential impact on musical creativity; presents broad coverage of this emerging, interdisciplinary area, from hard-core EEG analysis to practical musical applications.
This book discusses all aspects of computing for expressive performance, from the history of CSEMPs to the very latest research, in addition to discussing the fundamental ideas, and key issues and directions for future research. Topics and features: includes review questions at the end of each chapter; presents a survey of systems for real-time interactive control of automatic expressive music performance, including simulated conducting systems; examines two systems in detail, YQX and IMAP, each providing an example of a very different approach; introduces techniques for synthesizing expressive non-piano performances; addresses the challenges found in polyphonic music expression, from a statistical modelling point of view; discusses the automated analysis of musical structure, and the evaluation of CSEMPs; describes the emerging field of embodied expressive musical performance, devoted to building robots that can expressively perform music with traditional instruments.
In Knowledge-Based Programming for Music Research, Schaffer and McGee explore expert systems for applications in artificial intelligence (AI). The text concerns (1) basic principles for knowledge-based programming, (2) concepts and strategies for programming these systems, (3) a "universal data" model for music analysis, and (4) examples that concern specific aspects of design and application. The authors also investigate Prolog (programming in logic), one of the most widely used computer languages for AI, and base some of their applications on the recent implication-based theories of Eugene Narmour. Of the applications for programming a knowledge-based system, music analysis has the most potential. Beyond identifying isolated elements, it is possible to create programs that extend to chord structures and other, more complex structures. This kind of programming allows the authors to embed the rules of composition in the application and then extend the analysis throughout the musical work. It also allows them to arrive at the underlying principles for a given composition. As a tool for music analysis, such programming has profound implications for further growth. The text is designed for musicians at various levels and could also be used in courses on computer-music programming. Parts of the book have been successfully used in courses on computer programming for music research, with which the authors have direct experience. The text includes extensive examples of code for use in individual Prolog applications and a comprehensive bibliography.