Format: PDF / Kindle (mobi) / ePub
Musicians begin formal training by acquiring a body of musical concepts commonly known as musicianship. These concepts underlie the musical skills of listening, performance, and composition. Like humans, computer music programs can benefit from a systematic foundation of musical knowledge. This book explores the technology of implementing musical processes such as segmentation, pattern processing, and interactive improvisation in computer programs. It shows how the resulting applications can be used to accomplish tasks ranging from the solution of simple musical problems to the live performance of interactive compositions and the design of musically responsive installations and Web sites.
Machine Musicianship is both a programming tutorial and an exploration of the foundational concepts of musical analysis, performance, and composition. The theoretical foundations are derived from the fields of music theory, computer music, music cognition, and artificial intelligence. The book will be of interest to practitioners of those fields, as well as to performers and composers.
The concepts are programmed using C++ and Max. The accompanying CD-ROM includes working versions of the examples, as well as source code and a hypertext document showing how the code leads to the program's musical functionality.
Autonomic Computing: Concepts, Infrastructure, and Applications
Haptics: Perception, Devices and Scenarios: 6th International Conference, EuroHaptics 2008 Madrid, Spain, June 11-13, 2008, Proceedings (Lecture Notes ... Applications, incl. Internet/Web, and HCI)
Graph Databases: New Opportunities for Connected Data (2nd Edition)
Haptic Interaction with Deformable Objects: Modelling VR Systems for Textiles (Springer Series on Touch and Haptic Systems)
To the other pitches of the chord. As we know from acoustics, any pitched sound is composed of a number of frequencies that are related as integer multiples of the fundamental. The auditory system is so strongly tuned to this phenomenon that the brain will supply the fundamental to a set of integrally related frequencies that are missing the lowest member: we ‘‘hear’’ the missing fundamental as the pitch of the set even if it is not physically present. Figure 2.15 shows the harmonic series above.
Programs on their own. The accompanying CD-ROM includes working versions of the examples, as well as source code and a hypertext document showing how the code leads to the programs’ musical functionality. Machine Musicianship is not intended as a programming tutorial, however. The processes described in these pages constitute a computational approach to music analysis, composition, and performance that may engage practitioners in those fields whether they are programmers or not. I present the.
Examples that indicate a ‘‘pitch-class of resolution’’ for a given succession of pitch events, a network can learn to make such associations without the formulation of a wild proliferation of style- and period-dependent rule sets. 3.2 Time Structures To this point we have built symbolic and sub-symbolic processes for the real-time analysis of pitch structures. While music often can be dismantled into harmonic and rhythmic components, we clearly do not experience music as an assemblage of.
Grouping by accentuation of certain impulses as metrically ‘initiative’ ’’ (1987, 338). The criteria of accentuation he goes on to elaborate, then, can be read as a list of grouping markers. The accentuation criteria are grouped into three large classes ranked in order of importance. The first class of rules concern discontinuities between elements in which a superior value (accent) in some dimension follows a lesser value. For example, consider rule 1: Change to faster tempo. This criterion.
Machine performers can collaborate with an ensemble of other players. Chapter 8 looks at extensions of interactive environments to include other media, most prominently graphics, in live performance situations. Chapter 9 presents several interactive installations, where the inherent ability of such systems to deal with unpredictable input contributes to responsive environments exhibiting a variety of behaviors. A presentation of research directions form the conclusion in chapter 10. 1.5 Machine.