Sonification Examples for:
Relevance-based Interactive Optimization of Sonifications

Authors: Thomas Hermann, Kerstin Bunte, Helge Ritter

: International Conference on Auditory Display (ICAD 2007), Montreal, Canada, June, 2007

This paper presents a novel approach for the interactive optimization of sonification parameters. In a closed loop, the system automatically generates modified versions of an initial (or previously selected) sonification via gradient ascend or evolutionary algorithms. The human listener directs the optimization process by providing relevance feedback about the perceptual quality of these propositions. In summary, the scheme allows users to bring in their perceptual capabilities without burdening them with computational tasks. It also allows for continuous update of exploration goals in the course of an exploration task. Finally, Interactive Optimization is a promising novel paradigm for solving the mapping problems and for a user-centred design of auditory display. The paper gives a full account on the technique, and demonstrates the optimization at hand of synthetic and real-world data sets.
Article Link: HermannBunteRitter2007-RBI.pdf (available soon)

Sonification Examples

Fisher Data set (two overlapping clusters): The sonification examples are the parents of a series of optimization steps, starting with a random sonification and optimizing towards an audible separation of chlusters. SFk is the parent of iteration k.

Iris data set (4d data with 3 clusters, 150 items): The sonification examples are again the parents for the successive iterations during evolutionary optimization SIk denotes (S)ound Example for (I)ris data set iteration k.
The following examples are optimization results for increased attention to amplitude and panning

modified 2007-02-09, thermann(at)