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

TL;DR

ConversAR is an AR application that leverages embodied LLM agents to facilitate group conversations for second language learners, reducing anxiety and enhancing autonomous practice in immersive environments.

Contribution

This work introduces ConversAR, the first AR system enabling contextualized group language practice with embodied LLM agents, expanding beyond dyadic interactions.

Findings

Participants reported reduced speaking anxiety.

Participants experienced increased learner autonomy.

System demonstrated effective scene understanding and live captioning.

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.