Search Results for author:
Found 13 papers, 1 papers with code
AQ-GT: a Temporally Aligned and Quantized GRU-Transformer for Co-Speech Gesture Synthesis
By learning the mapping of a latent space representation as opposed to directly mapping it to a vector representation, this framework facilitates the generation of highly realistic and expressive gestures that closely replicate human movement and behavior, while simultaneously avoiding artifacts in the generation process.
Ranked #1 on
Gesture Generation
on TED Gesture Dataset
Automatic Error Analysis of Human Motor Performance for Interactive Coaching in Virtual Reality
The selected features are used as input for Support Vector Machines, which finally classify the movement errors.
A predictive processing model of perception and action for self-other distinction
During interaction with others, we perceive and produce social actions in close temporal distance or even simultaneously.
Enabling robust and fluid spoken dialogue with cognitively impaired users
We present the flexdiam dialogue management architecture, which was developed in a series of projects dedicated to tailoring spoken interaction to the needs of users with cognitive impairments in an everyday assistive domain, using a multimodal front-end.
ALICO: a multimodal corpus for the study of active listening
The Active Listening Corpus (ALICO) is a multimodal database of spontaneous dyadic conversations with diverse speech and gestural annotations of both dialogue partners.
Satisficing Mentalizing: Bayesian Models of Theory of Mind Reasoning in Scenarios with Different Uncertainties
The ability to interpret the mental state of another agent based on its behavior, also called Theory of Mind (ToM), is crucial for humans in any kind of social interaction.
Resonating Minds -- Emergent Collaboration Through Hierarchical Active Inference
The results indicate that belief resonance and active inference allow for quick and efficient agent coordination, and thus can serve as a building block for collaborative cognitive agents.
Towards autonomous artificial agents with an active self: modeling sense of control in situated action
In particular we focus on how an agent can be equipped with a sense of control and how it arises in autonomous situated action and, in turn, influences action control.
Addressing Data Scarcity in Multimodal User State Recognition by Combining Semi-Supervised and Supervised Learning
Detecting mental states of human users is crucial for the development of cooperative and intelligent robots, as it enables the robot to understand the user's intentions and desires.
