SOMson -- Sonification of Multidimensional Data in Kohonen Maps

arXiv:2404.00016v1 Announce Type: cross
Abstract: Kohonen Maps, aka. Self-organizing maps (SOMs) are neural networks that visualize a high-dimensional feature space on a low-dimensional map. While SOMs are an excellent tool for data examination and exploration, they inherently cause a loss of detail. Visualizations of the underlying data do not integrate well and, therefore, fail to provide an overall picture. Consequently, we suggest SOMson, an interactive sonification of the underlying data, as a data augmentation technique. The sonification increases the amount …

abstract arxiv cs.hc cs.lg data exploration feature loss low map maps multidimensional networks neural networks sonification space tool type