ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners
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.
Jad Bendarkawi、Ashley Ponce、Sean Mata、Aminah Aliu、Yuhan Liu、Lei Zhang、Amna Liaqat、Varun Nagaraj Rao、Andrés Monroy-Hernández
语言学计算技术、计算机技术
Jad Bendarkawi,Ashley Ponce,Sean Mata,Aminah Aliu,Yuhan Liu,Lei Zhang,Amna Liaqat,Varun Nagaraj Rao,Andrés Monroy-Hernández.ConversAR: Exploring Embodied LLM-Powered Group Conversations in Augmented Reality for Second Language Learners[EB/OL].(2025-05-29)[2025-07-16].https://arxiv.org/abs/2505.24000.点此复制
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