(Georgia Institute of Technology, 2014-06)
Vicinanza, Domenico; Stables, Ryan; Clemens, Graeme; Baker, Matthew
In this study we investigate ways in which data sonification can
improve standard data analysis techniques currently employed in
the analysis of stem-cells using Fourier Transform Infrared (FTIR)
Spectroscopy. Four different sonification methods have been evaluated
and their effectiveness has been evaluated through listening
tests, designed to assess the discriminating capability of the
auditory technique. We identify FM synthesis driven by feature
extraction as the most perceptually relevant technique for the auditory
classification of FTIR data. Whilst this technique is not
commonly used in sonification research, it allows us to utilise the
most salient characteristics of the absorption spectra, leading to an
improved classification accuracy with a clear timbral differences
between differentiated and non-differentiated cell-types.