An Enhanced Data Transformation Framework for the Sonification of Simulated Rigid Bodies
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While simulated rigid bodies hold a wealth of information that can be understood through sound (Table 1), current interpretive methods will often overlook important features of their data. This proves to be detrimental when placing the same data in the context of an auditory display where the user might wish to analyse or express specific dimensions under a range of circumstances. The following investigation describes a framework for a model-induced parameter mapping technique which allows for an explicit level of control over the flow of information, supported by a number of key conditions in both the auditory and visual channels. Given that the formative decisions behind this design tailors the data to meet the purposes of sonification, the user is presented with a viable alternative that overcomes a number of limitations inherent to employing a more conventional physical modelling approach.