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Sames Al Moubayed

dblp:97/7736 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 50% Human-AI interaction · 50%
Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction
conversational agents
0.112009
Generating Robot/Agent backchannels during a storytelling experiment · ICRA 2009
Haptics and multimodal interaction
multimodal interaction
0.112009
Generating Robot/Agent backchannels during a storytelling experiment · ICRA 2009
Multimedia analysis and retrieval › multimedia dataset construction › multimodal dataset
multimodal corpus
0.012009
Generating Robot/Agent backchannels during a storytelling experiment · ICRA 2009

Methods — techniques the papers use, named apart from their topics

behavior modeling · 0.2
YearPublicationVenuePosition
2009 Generating Robot/Agent backchannels during a storytelling experiment
abstract
This work presents the development of a real-time framework for the research of multimodal feedback of robots/talking agents in the context of Human Robot Interaction (HRI) and Human Computer Interaction (HCI). For evaluating the framework, a Multimodal corpus is built (ENTERFACE_STEAD), and a study on the important multimodal features was done for building an active Robot/Agent listener of a storytelling experience with Humans. The experiments show that even when building the same reactive behavior models for Robot and Talking Agents, the interpretation and the realization of the behavior communicated is different due to the different communicative channels Robots/Agents offer be it physical but less human-like in Robots, and virtual but more expressive and human-like in Talking agents.
Sames Al Moubayed, Malek Baklouti, Mohamed Chetouani, Thierry Dutoit, Ammar Mahdhaoui, Jean-Claude Martin, Stanislav Ondás, Catherine Pelachaud, Jérôme Urbain
ICRA1