Maha Salem,
"Effects of Humanlike Conversational Behavior on the Perception of Psychological Anthropomorphism: A Case Study with a Humanoid Robot",
ICSR 2011 : International Conference on Social Robotics 2011, 2011.
Abstract
Previous work has shown that typically human conversa- tional behaviors such as gesturing increase anthropomorphic inferences about artificial communicators such as virtual agents. In an experiment with a humanoid robot, we investigated how far humanlike gesturing be- havior would affect anthropomorphic inferences about the robot. Partic- ularly, we examined the effects of the robot’s gesturing behaviors on the attribution of typically human tr...
Download Bibtex file
Download PDF
Sven Hellbach, Christian Vollmer, Julian Eggert, Horst-Michael Groß,
"Learning Motion Primitives using Spatio-Temporal NMF",
Proc. of the DAGM Workshop "New Challenges in Neural Computation" 2011, Machine Learning Reports 05/11, 2011.
Download Bibtex file
Download PDF
Martin Heckmann and Claudius Gläser,
"Discriminant Sub-Space Projection of Spectro-Temporal Speech Features based on Maximizing Mutual Information",
Proc. INTERSPEECH, 2011.
Abstract
We previously developed noise robust Hierarchical Spectro-Temporal (HIST) speech features. The learning of the features was performed in an unsupervised way with unlabeled speech data. In a final stage we deployed Principal Component Analysis (PCA) to reduce the feature dimensions and to diagonalize them. In this paper we investigate if a discriminant projection can further increase the performance. We maximize the mutual information between the ...
Download Bibtex file
Download PDF
Martin Heckmann, Xavier Domont, Frank Joublin, Christian Goerick,
"A Hierarchical Framework for Spectro-Temporal Feature Extraction",
Speech Communication, vol. 53, no. 5, pp. 736 - 752, 2011.
Abstract
In this paper we present a hierarchical framework for the extraction of spectro-temporal acoustic features. The design of the features targets higher robustness in dynamic environments. Motivated by the large gap between human and machine performance in such conditions we take inspirations from the organization of the mammalian auditory cortex in the design of our features. This includes the joint processing of spectral and temporal information, ...
Download Bibtex file
Download PDF
Nils Einecke, Manuel Mühlig, Jens Schmüdderich, Michael Gienger,
""Bring it to me" - Generation of Behavior-Relevant Scene Elements for Interactive Robot Scenarios",
Proceedings of the IEEE International Conference on Robotics and Automation, 2011.
Abstract
Humanoid robots are intended to act and interact in dynamically changing environments in the presence of humans. Current robotic systems are usually able to move in dynamically changing environments because of an inbuilt depth and obstacle sensing. However, for acting in their environment the internal representation of such systems is usually constructed by hand and known in advance. In contrast in this paper, we present a system that dynamically...
Download Bibtex file
Download PDF
Michael Rath,
"Information Theoretic Approach to the Investigation of Design and Flow Feature Interactions",
TU Darmstadt, 2011.
Download Bibtex file
Per Mail Request
Anna-Lisa Vollmer,
"Measurement and Analysis of Interactive Behavior in Tutoring Action with Children and Robots",
University of Bielefeld, 2011.
Download Bibtex file
Per Mail Request
Robert Kastner, Thomas Michalke, Jürgen Adamy, Jannik Fritsch, Christian Goerick,
"Task-Based Environment Interpretation and System Architecture for Next Generation ADAS",
IEEE Intelligent Transportation Systems Magazine,, vol. 3, no. 4, pp. 20–33, 2011.
Download Bibtex file
Download PDF
Florian Hauser, Andreas Knoblauch, Günther Palm,
"A simulation study on different STDP models concerning localized gamma oscillations.",
Frontiers in Systems Neuroscience. Conference Abstract: Computational and Systems Neuroscience, 2011.
Download Bibtex file
Download PDF
Claudius Gläser and Frank Joublin,
"Firing Rate Homeostasis for Dynamic Neural Field Formation",
IEEE Transactions on Autonomous Mental Development, 2011.
Abstract
Dynamic neural fields are recurrent neural networks which aim at modeling cortical activity evolution both in space and time. A self-organized formation of these fields has been rarely explored previously. The main reason for this is that learning-induced changes in effective connectivity constitute a severe problem with respect to network stability. In this paper we present a novel network model which is able to self-organize even in face of exp...
Download Bibtex file
Download PDF
1 ...
91 92 93 94
95 96 ...
151
