Sonification, which is the conversion of physical data (temperature, network traffic, or an electrocardiogram) into sound, is very suitable for augmenting task monitoring. The challenge to the sound designer is to create a monitoring display that maximizes the conveyed information while at the same time remaining unobtrusive. In this article an auditory augmentation approach was developed for monitoring evolutionary optimization algorithms. In order to augment short interaction sounds effectively with the information about the high-dimensional search space, a sonification method known as data sonograms was applied. Various mappings of data to sound features have been investigated, where the delay of the signal has been shown to be an interesting parameter that plays a role in both unobtrusiveness and information conveyed.
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