International Conference on Auditory Display (ICAD)

Series

International Conference on Auditory Display (ICAD)

Permanent Link

https://hdl.handle.net/1853/70916

Series Type

Event Series

Associated Organization(s)

Organizational Unit

Sonification Lab

Full item page

Publication Search Results

Now showing 1 - 8 of 8

Tangible data scanning sonification model

(Georgia Institute of Technology, 2006-06) Bovermann, T. ; Hermann, T. ; Ritter, H.

In this paper we develop a sonification model following the Modelbased Sonification approach that allows to scan high-dimensional data distributions by means of a physical object in the hand of the user. In the sonification model, the user is immersed in a 3D space of invisible but acoustically active objects which can be excited by him. Tangible computing allows to identify the excitation object (e.g. a geometric surface) with a physical object used as controller, and thus creates a strong metaphor for understanding and relating feedback sounds in response to the user's own activity, position and orientation. We explain the technique and our current implementation in detail and give examples at hand of synthetic and real-world data sets.
Vocal sonification of pathologic EEG features

(Georgia Institute of Technology, 2006-06) Hermann, T. ; Baier, G. ; Stephani, U. ; Ritter, H.

We introduce a novel approach in EEG data sonification for process monitoring and exploratory as well as comparative data analysis. The approach uses an excitory/articulatory speech model and a particularly selected parameter mapping to obtain auditory gestalts (or auditory objects) that correspond to features in the multivariate signals. The sonification is adaptable to patient-specific data patterns, so that only characteristic deviations from background behavior (pathologic features) are involved in the sonification rendering. Thus the approach combines data mining techniques and case-dependent sonification design to give an application-specific solution with high potential for clinical use. We explain the sonification technique in detail and present sound examples from clinical data sets.
A malleable device with applications to sonification-based data exploration

(Georgia Institute of Technology, 2006-06) Milczynski, M. ; Hermann, T. ; Bovermann, T. ; Ritter, H.

This article introduces a novel human computer interaction device, developed in the scope of a Master's Thesis. The device allows continuous localized interaction by providing a malleable interaction surface. Diverse multi-finger as well as multi-handed manipulations can be applied. Furthermore, the device acts as a tangible user interface object, integrated into a tangible computing framework called tDesk. Software to convert the malleable element's shape into an internal surface representation has been developed. Malleable interactions are applied to a new Modelbased Sonification approach for exploratory data analysis. Highdimensional data are acoustically explored via their informative interaction sound in result to the user's excitation.
Sonified epileptic rhythms

(Georgia Institute of Technology, 2006-06) Baier, G. ; Hermann, T. ; Sahle, S. ; Stephani, U.

We describe techniques to sonify rhythmic activity of epileptic seizures as measured by human EEG. Eventbased mapping of parameters is found to be informative in terms of auto- and cross-correlations of the multivariate data. For the study, a group of patients with childhood absence seizures are selected. We find consistent intra-patient conservation of the rhythmic pattern as well as inter-patient variations, especially in terms of cross-correlations. The sound synthesis is suitable for online sonification. Thus, the application of the proposed sonification in clinical monitoring is possible.
The importance of interaction in sonification

(Georgia Institute of Technology, 2004-07) Hermann, T. ; Hunt, A.

This paper argues for a special focus on the use of dynamic human interaction to explore datasets while they are being transformed into sound. We describe why this is a special case of both human computer interaction (HCI) techniques and sonification methods. Humans are adapted for interacting with their physical environment and making continuous use of all their senses. When this exploratory interaction is applied to a dataset (by continuously controlling its transformation into sound) new insights are gained into the data's macro and micro-structure, which are not obvious in a visual rendering. This paper reviews the importance of interaction in sonification, describes how a certain quality of interaction is required, provides examples of the techniques being applied interactively, and outlines a plan of future work to develop interaction techniques to aid sonification.
The sonification of rhythms in human electroencephalogram

(Georgia Institute of Technology, 2004-07) Hermann, T. ; Baier, G.

We use sonification of temporal information extracted from scalp EEG to characterize the dynamic properties of rhythms in certain frequency bands. Sonification proves particularly useful in the simultaneous monitoring of several EEG channels. Our results suggest sonification as an important tool in the analysis of multivariate data with subtle correlation differences.
Crystallization sonification of high-dimensional datasets

(Georgia Institute of Technology, 2002-07) Ritter, H. ; Hermann, T.

This paper introduces Crystallization Sonification, a sonification model for exploratory analysis of high-dimensional datasets. The model is designed to provide information about the intrinsic data dimensionality (which is a local feature) and the global data dimensionality, as well as the transitions between a local and global view on a dataset. Furthermore the sound allows to display the clustering in high-dimensional datasets. The model defines a crystal growth process in the high-dimensional data-space which starts at a user selected ``condensation nucleus'' and incrementally includes neighboring data according to some growth criterion. The sound summarizes the temporal evolution of this crystal growth process. For introducing the model, a simple growth law is used. Other growth laws which are used in the context of hierarchical clustering are also suited and their application in crystallization sonification offers new ways to inspect the results of data clustering as an alternative to dendrogram plots. In this paper, the sonification model is described and example sonifications are presented for some synthetic high-dimensional datasets.
Sonifications for EEG data analysis

(Georgia Institute of Technology, 2002-07) Hermann, T. ; Meinicke, P. ; Bekel, H. ; Ritter, H. ; Mueller, H. M. ; Weiss, S.

This paper presents techniques to render acoustic representations for EEG data. In our case, data are obtained from psycholinguistic experiments where subjects are exposed to three different conditions based on different auditory stimuli. The goal of this research is to uncover elements of neural processing correlated with high-level cognitive activity. Three sonifications are presented within this paper: spectral mapping sonification which offers a quite direct inspection of the recorded data, distance matrix sonification which allows to detect nonlinear long range correlations at high time resolution, and differential sonification which summarizes the comparison of EEG measurements under different conditions for each subject. This paper describes the techniques and presents sonification examples for experimental data.