Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents

Fuente: arXiv
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Main Authors: Arjmand, Mehdi, Nouraei, Farnaz, Steenstra, Ian, Bickmore, Timothy
Format: Preprint
Published: 2024
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author Arjmand, Mehdi
Nouraei, Farnaz
Steenstra, Ian
Bickmore, Timothy
author_facet Arjmand, Mehdi
Nouraei, Farnaz
Steenstra, Ian
Bickmore, Timothy
contents We introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion includes listener empathy for the speaker's affective state. Empathic grounding is generally required whenever the speaker's emotions are foregrounded and can make the grounding process more efficient and reliable by communicating both propositional and affective understanding. Both speaker expressions of affect and listener empathic grounding can be multimodal, including facial expressions and other nonverbal displays. Thus, models of empathic grounding for embodied agents should be multimodal to facilitate natural and efficient communication. We describe a multimodal model that takes as input user speech and facial expression to generate multimodal grounding moves for a listening agent using a large language model. We also describe a testbed to evaluate approaches to empathic grounding, in which a humanoid robot interviews a user about a past episode of pain and then has the user rate their perception of the robot's empathy. We compare our proposed model to one that only generates non-affective grounding cues in a between-subjects experiment. Findings demonstrate that empathic grounding increases user perceptions of empathy, understanding, emotional intelligence, and trust. Our work highlights the role of emotion awareness and multimodality in generating appropriate grounding moves for conversational agents.
format Preprint
id arxiv_https___arxiv_org_abs_2407_01824
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents
Arjmand, Mehdi
Nouraei, Farnaz
Steenstra, Ian
Bickmore, Timothy
Human-Computer Interaction
Computation and Language
Robotics
We introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion includes listener empathy for the speaker's affective state. Empathic grounding is generally required whenever the speaker's emotions are foregrounded and can make the grounding process more efficient and reliable by communicating both propositional and affective understanding. Both speaker expressions of affect and listener empathic grounding can be multimodal, including facial expressions and other nonverbal displays. Thus, models of empathic grounding for embodied agents should be multimodal to facilitate natural and efficient communication. We describe a multimodal model that takes as input user speech and facial expression to generate multimodal grounding moves for a listening agent using a large language model. We also describe a testbed to evaluate approaches to empathic grounding, in which a humanoid robot interviews a user about a past episode of pain and then has the user rate their perception of the robot's empathy. We compare our proposed model to one that only generates non-affective grounding cues in a between-subjects experiment. Findings demonstrate that empathic grounding increases user perceptions of empathy, understanding, emotional intelligence, and trust. Our work highlights the role of emotion awareness and multimodality in generating appropriate grounding moves for conversational agents.
title Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents
topic Human-Computer Interaction
Computation and Language
Robotics
url https://arxiv.org/abs/2407.01824