ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners

Group conversations are valuable for second language (L2) learners as they provide opportunities to practice listening and speaking, exercise complex turn-taking skills, and experience group social dynamics in a target language. However, most existing Augmented Reality (AR)-based conversational learning tools focus on dyadic interactions rather than group dialogues. Although research has shown that AR can help reduce speaking anxiety and create a comfortable space for practicing speaking skills in dyadic scenarios, especially with Large Language Model (LLM)-based conversational agents, the potential for group language practice using these technologies remains largely unexplored. We introduce ConversAR, a gpt-4o powered AR application, that enables L2 learners to practice contextualized group conversations. Our system features two embodied LLM agents with vision-based scene understanding and live captions. In a system evaluation with 10 participants, users reported reduced speaking anxiety and increased learner autonomy compared to perceptions of in-person practice methods with other learners.

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Publication Details

Published
2025-04-23
DOI
https://doi.org/10.1145/3706599.3720162
Citations
2
Primary Topic
Speech and dialogue systems
Type
article
Field-Weighted Citation Impact
4.96
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article

ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners

Sean Chidozie Mata, Andrés Monroy‐Hernández, Lei Zhang, Alejandro A. Pérez Ponce et al.
2 citations
Speech and dialogue systems
4.96
article

ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners

Sean Chidozie Mata, Andrés Monroy‐Hernández, Lei Zhang, Alejandro A. Pérez Ponce, Amna Liaqat, Varun Nagaraj Rao, Yuhan Liu, Jad Bendarkawi, Aminah Aliu
article en
2 citations

Abstract

Group conversations are valuable for second language (L2) learners as they provide opportunities to practice listening and speaking, exercise complex turn-taking skills, and experience group social dynamics in a target language. However, most existing Augmented Reality (AR)-based conversational learning tools focus on dyadic interactions rather than group dialogues. Although research has shown that AR can help reduce speaking anxiety and create a comfortable space for practicing speaking skills in dyadic scenarios, especially with Large Language Model (LLM)-based conversational agents, the potential for group language practice using these technologies remains largely unexplored. We introduce ConversAR, a gpt-4o powered AR application, that enables L2 learners to practice contextualized group conversations. Our system features two embodied LLM agents with vision-based scene understanding and live captions. In a system evaluation with 10 participants, users reported reduced speaking anxiety and increased learner autonomy compared to perceptions of in-person practice methods with other learners.

Princeton University (US)
Quality Education
Openalex Percentile: Top 6%
Speech and dialogue systems
4.96
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ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners — Sean Chidozie Mata, Andrés Monroy‐Hernández, et al. · (2025) | TGRS Research Map | TGRS