Papers by Cristian-Paul Bara

3 papers
MuSE: a Multimodal Dataset of Stressed Emotion (2020.lrec-1)

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Challenge: Existing studies on the effects of stress and emotion on the production and perception of emotion are understudied.
Approach: They propose to use a multimodal stressed emotion dataset to study the interplay between the presence of stress and expressions of affect.
Outcome: The proposed dataset combines emotion and stress classification with annotations for the emotional content of the recordings.
MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks (2021.emnlp-main)

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Challenge: Creating embodied, situated agents able to move in, communicate naturally about, and collaborate on human terms in the physical world has been a persisting goal in artificial intelligence (Winograd, 1972).
Approach: They propose to use a 3D Minecraft dataset to model the beliefs of human partners in situ to enable theory of mind modeling in situated interactions.
Outcome: The proposed model can be used to model human collaborative behaviors in the 3D virtual blocks world of Minecraft.
DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents (2022.findings-emnlp)

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Challenge: Empowering autonomous driving agents with the ability to navigate in a continuous and dynamic environment is critical.
Approach: They propose a novel interactive simulation platform that enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.
Outcome: The proposed platform enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.

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