Non-native speakers (NNSs) face significant language barriers in multilingual communication with native speakers (NSs). While AI-mediated communication (AIMC) tools offer efficient one-time assistance, they often overlook opportunities for NNSs' continuous language acquisition. We introduce ChatLearn, an enhanced AIMC system that leverages NNSs' communication difficulties as learning opportunities. Beyond comprehension and expression assistance, ChatLearn simultaneously captures NNSs' language challenges, and subsequently provides them with spaced review as the conversation progresses. We conducted a mixed-methods study using a communication task with 43 NNS-NS pairs, after which ChatLearn NNSs recalled significantly more expressions than the baseline group, while there was no substantial decline in communication experience. Our findings highlight the value of contextual learning in NNS-NS communication, providing a new direction for AIMC systems that foster both immediate collaboration and continuous language development.

翻译：非母语者在与母语者进行多语言交流时面临显著的语言障碍。虽然人工智能辅助沟通工具能提供高效的一次性帮助，但往往忽视了非母语者持续语言习得的机会。我们提出ChatLearn——一个增强型人工智能辅助沟通系统，该系统将非母语者的沟通困难转化为学习机遇。除理解与表达辅助外，ChatLearn能实时捕捉非母语者的语言难点，并随着对话进程为其提供间隔复习。我们采用混合研究方法，通过43组非母语者-母语者配对完成交流任务进行实验。结果显示，使用ChatLearn的非母语者比对照组能回忆起更多表达方式，且沟通体验未出现显著下降。我们的研究揭示了情境学习在非母语者-母语者交流中的重要价值，为人工智能辅助沟通系统的发展提供了新方向——既能促进即时协作，又能支持持续语言发展。