Supplementary Material for "Growing Neural Gas Sonification Model for Interactive Surfaces"

In this paper we present our reimplementation of the Growing Neural Gas Sonification for interactive surfaces such as our t-Desk or touch-capable tablet PCs. Growing Neural Gas (GNG) is an undirected learning algorithm that incrementally 'grows' a network graph into data distributions, revealing the data distributions' intrinsic dimensionality and aspects of its structure. The GNG Sonification (GNGS) provides a method to interactively explore the GNG during the growing process, utilizing a Model- Based Sonification (MBS) to convey audible information about the data distribution in addition to the visualization. The goal of our reimplementation was to be able to rapidly grasp the structure of the sonified and visualized data, to give the user the ability to conduct direct A/B comparisons between different (or similar) clusters within a data distribution. The direct bi-manual interaction as well as a simplified full-screen touchable user interface helps to focus on the exploration of the GNG rather than the interaction itself. We present and discuss different interaction metaphors for the excitation of the model setup in this MBS. #### Quiz #### Snake #### Three Cluster #### Video Example 1 #### Video Example 2 #### Video Example 3

本研究提出了针对交互式界面（如本团队的t-Desk或支持触控的平板电脑）的生长神经气体声化（Growing Neural Gas Sonification）重实现方案。生长神经气体（Growing Neural Gas, GNG）是一种无向增量学习算法，可逐步将网络图“生长”至数据分布中，从而揭示数据分布的本征维度与结构特征。生长神经气体声化（GNG Sonification, GNGS）提供了一种在生长过程中交互式探索GNG的方法，其借助基于模型的声化（Model-Based Sonification, MBS），在可视化之外同步传递数据分布的听觉信息。本次重实现的目标在于让使用者能够快速掌握经声化与可视化处理的数据的结构，并支持用户直接对数据分布内不同（或相似）的簇开展A/B对比实验。双手直接交互配合简化的全屏触控用户界面，有助于使用者将注意力聚焦于GNG的探索过程，而非交互操作本身。本研究还介绍并讨论了在该MBS中激活模型配置的多种交互隐喻。#### Quiz #### Snake #### Three Cluster #### Video Example 1 #### Video Example 2 #### Video Example 3