Learning another language can be a highly emotional process, typically characterized by numerous frustrations and triumphs, big and small. For most learners, language learning does not follow a linear, predictable path, its zigzag course shaped by motivational (or demotivating) variables such as personal characteristics, teacher/peer relationships, learning materials, and dreams of a future L2 (second language) self. While some aspects of language learning (reading, grammar) are relatively mechanical, others can be stressful and unpredictable, especially conversing in the target language. That experience necessitates not only knowledge of structure and lexis, but also the ability to use the language in ways that are appropriate to the social and cultural context. A new opportunity to practice conversational abilities has arrived through the availability of AI chatbots, with both advantages (responsive, non-judgmental) and drawbacks (emotionally void, culturally biased). This column explores aspects of emotion as they arise in technology use and in particular how automatic emotion recognition and simulated human responsiveness in AI systems interface with language learning and the development of pragmatic and interactional competence. Emotion AI, the algorithmically driven interpretation of users' affective signals, has been seen as enabling greater personalized learning, adapting to perceived learner cognitive and emotional states. Others warn of emotional manipulation and inappropriate and ineffective user profiling

翻译：学习另一门语言是一种高度情感化的过程，通常伴随着大大小小的挫折与成功。对大多数学习者而言，语言学习并非一条线性、可预测的路径，其曲折轨迹受到个人特质、师生关系、学习材料以及对未来第二语言（L2）自我憧憬等激励（或阻碍）变量的影响。虽然语言学习的某些方面（如阅读、语法）相对具有机械性，但其他方面，尤其是用目标语言进行对话，可能充满压力且不可预测。这一体验不仅要求学习者掌握结构与词汇知识，还需具备在特定社会文化语境中恰当使用语言的能力。人工智能聊天机器人的普及为练习会话技能提供了新机遇，其优势（如响应及时、不带评判性）与劣势（如缺乏情感、存在文化偏见）并存。本文探讨了技术使用中产生的情感问题，特别是自动情感识别与人工智能系统的拟人化响应如何影响语言学习以及语用与互动能力的发展。情感人工智能——通过算法驱动对用户情感信号的解读——被认为能够增强个性化学习，适应感知到的学习者认知与情感状态。与此同时，也有人警示情感操控以及不当、无效的用户画像分析可能带来的风险。