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Perkins, Rhys John (2013)
Languages: English
Types: Doctoral thesis
Physics engines have become increasingly prevalent in everyday technology. In the context of this thesis they are regarded as a readily available data set that has the potential to intuitively present the process of sonification to a wide audience. Unfortunately, this process is not the focus of attention when formative decisions are made concerning the continued development of these engines. This may reveal a missed opportunity when considering that the field of interactive sonification upholds the importance of physical causalities for the analysis of data through sound. The following investigation deliberates the contextual framework of this field to argue that the physics engine, as part of typical game engine architecture, is an appropriate foundation on which to design and implement a dynamic toolset for interactive sonification. The basis for this design is supported by a number of significant theories which suggest that the underlying data of a rigid body dynamics physics system can sustain an inherent audiovisual metaphor for interaction, interpretation and analysis. Furthermore, it is determined that this metaphor can be enhanced by the extraordinary potential of the computer in order to construct unique abstractions which build upon the many pertinent ideas and practices within the surrounding literature. These abstractions result in a mental model for the transformation of data to sound that has a number of advantages in contrast to a physical modelling approach while maintaining its same creative potential for instrument building, composition and live performance. Ambitions for both sonification and its creative potential are realised by several components which present the user with a range of options for interacting with this model. The implementation of these components effectuates a design that can be demonstrated to offer a unique interpretation of existing strategies as well as overcoming certain limitations of comparable work.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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