Authors: Thomas Hermann, Helge Ritter
Proceedings of the International Symposium on Non-visual & Multimodal Visualization, July 2004, London, UK, submitted
Sound Examples: GNGS -- Probing Gaussian Distributions
The sonifications are currently computed offline: after a click in a
scatterplot of the data the nearest neuron of the GNG is searched and the
graph is excited at this location. Since energy propagates along
topological connections between the GNG graph, the sound is completely
determined from a connected subgraph, e.g. a cluster. The sonifications
last about 2 secs, and are presented to the listener as soon as they are
computed. Since this interrupts the exploratory flow only slightly, the
user is appearing an (discrete) interactive mode of exploration.
Sonifications for probing in the clusters of intrinsic dimension d:
Sound Examples: GNGS -- Probing Sonification for the Noisy Spiral dataset
A noisy spiral dataset is adapted by a GNG. This are GNGS probing
sonifications from (a) the outer end of the spiral, (b) in the middle, (c)
the inner end of the spiral. The examples are for differing network
complexity, expressed by the number of neurons N.
Sound Examples: GNGS -- Process Monitoring Sonifications
The following for sonification present the dynamically changing auditory
state of a GNG during the adaptive growth process.
Sound Examples: GNGS Probing and Process Monitoring for MNIST dataset
The MNIST dataset contains 24x24 pixel bitmaps of handwritten digits.
8x8 subsampling was performed to obtain 64-dimensional records, about 1000
records for each class. The examples are computed for the classes of '1'
and '2'. The shape of '2' contains more internal degrees of freedom,
resulting in a higher intrinsic dimensionality of the distribution, audible
from the higher brilliance and complexity of the probing sonification.