Abstract
Self-aware and self-expressive technologies may be used to improve user experience in interactive music systems. This chapter presents how the concepts and techniques from the first parts of the book may be exploited to develop better technologies for active music. Nature-inspired and socially-inspired methods, as introduced in Chapter 7, are used to allow music listeners to influence high-level parameters of the music, such as mood or tempo, without requiring the skill of a professional musician. Several of the examples presented in this chapter utilise the same algorithms as presented for the multi-camera networks in Chapter 13, thus demonstrating the broad application domain of these algorithms. The chapter is organised as a discussion of three example systems. First, a mechanism for conflict resolution in a distributed active music system is presented. The second and third example presented take inspiration from the pheromone mechanism used in Ant Colony Optimisation. The approach is first used for continuous classification of the movement patterns of listeners to incorporate adaptive mapping between sensor data and musical output. In the third example the same mechanism enables a system to remember the preferences of a user when navigating in a musical space.
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© 2016 Springer International Publishing Switzerland
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Nymoen, K., Chandra, A., Torresen, J. (2016). Self-awareness in Active Music Systems. In: Lewis, P., Platzner, M., Rinner, B., Tørresen, J., Yao, X. (eds) Self-aware Computing Systems. Natural Computing Series. Springer, Cham. https://doi.org/10.1007/978-3-319-39675-0_14
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DOI: https://doi.org/10.1007/978-3-319-39675-0_14
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