Non-native speakers (NNSs) frequently encounter speaking difficulties in multilingual communication, where existing approaches have shown promise in facilitating NNSs' comprehension and participation in real-time communication. However, they often overlook providing direct speaking support, where anxiety stemming from linguistic inadequacy and uncertain communication dynamics are core issues. To address this, we introduce an AI tool with translation for real-time speaking support. It also builds a channel for mutual understanding with native speakers (NSs) to mitigate interactional anxiety. Through a within-subjects experiment involving 25 NNS-NS pairs (N = 50) on collaborative tasks, our findings suggest that the tool improved NNSs' speaking self-efficacy, reduced their interactional anxiety, and decreased their workload, particularly for NNSs with below-average language proficiency. Furthermore, NNSs reported a significant sense of support from their NS partners via the mutual understanding channel, and NSs also clearly perceived the NNSs' need for assistance and displayed a strong sense of communicative responsibility. This research underscores the potential of AI support in real-time NNS communication and the importance of promoting mutual understanding, culminating in actionable design insights for future work.

翻译：非母语者在多语交流中常面临口语表达困难，现有方法虽能促进其理解并参与实时交流，但往往忽视直接提供口语支持——语言能力不足与不确定的交流动态所引发的焦虑是核心问题。为此，我们引入了一款集成翻译功能的AI工具，以提供实时口语支持；同时构建了与母语者相互理解的通道以缓解互动焦虑。通过一项涉及25组非母语者-母语者配对（共50人）的协作任务被试内实验，结果表明该工具提升了非母语者的口语自我效能感，降低了其互动焦虑和工作负荷，尤其对语言水平低于平均值的非母语者效果显著。此外，非母语者通过相互理解通道感受到来自母语伙伴的显著支持，而母语者也清晰感知到非母语者的求助需求并展现出强烈的沟通责任感。本研究凸显了AI支持在非母语者实时交流中的潜力，以及促进相互理解的重要性，最终为未来研究提供了可操作的设计洞见。