TwIPS：一个由大语言模型驱动的短信应用，旨在为自闭症用户简化对话中的微妙含义
TwIPS: A Large Language Model Powered Texting Application to Simplify Conversational Nuances for Autistic Users
AI总结：
提出大语言模型驱动的短信应用TwIPS，通过解读消息语气、校准情感意图及提供替代表达，有效辅助自闭症用户克服文本沟通障碍并促进反思。
摘要：
自闭症患者通常在传达和解读情感语气及非字面微妙含义方面存在困难。许多人也会掩饰自己的沟通风格以避免被他人误解，在此过程中耗费大量时间和精力。为了解决基于文本沟通中的这些挑战，我们提出了TwIPS，这是一个由大语言模型（LLM）驱动的短信应用原型，它可以协助用户：a) 解读接收消息的语气和含义，b) 确保其消息的情感语气符合其意图，以及 c) 为可能被误解并受到他人负面反馈的消息提供替代表达。我们利用基于AI的模拟和对话脚本，在实验室环境中对8名自闭症参与者进行了TwIPS评估。研究结果表明，TwIPS为参与者提供了一种寻求澄清的便捷方式，提供了比语气指示器更好的替代方案，并促进了对写作技巧和风格的建构性反思。我们还研究了自闭症用户在即时通讯中如何利用语言进行自我表达和解读，并收集了改进原型的反馈。最后，我们讨论了在AI辅助沟通背景下，如何平衡用户自主性与AI介入、在AI系统中建立适当信任水平，以及自闭症用户的定制需求。
英文摘要：
Autistic individuals often experience difficulties in conveying and interpreting emotional tone and non-literal nuances. Many also mask their communication style to avoid being misconstrued by others, spending considerable time and mental effort in the process. To address these challenges in text-based communication, we present TwIPS, a prototype texting application powered by a large language model (LLM), which can assist users with: a) deciphering tone and meaning of incoming messages, b) ensuring the emotional tone of their message is in line with their intent, and c) coming up with alternate phrasing for messages that could be misconstrued and received negatively by others. We leverage an AI-based simulation and a conversational script to evaluate TwIPS with 8 autistic participants in an in-lab setting. Our findings show TwIPS enables a convenient way for participants to seek clarifications, provides a better alternative to tone indicators, and facilitates constructive reflection on writing technique and style. We also examine how autistic users utilize language for self-expression and interpretation in instant messaging, and gather feedback for enhancing our prototype. We conclude with a discussion around balancing user-autonomy with AI-mediation, establishing appropriate trust levels in AI systems, and customization needs if autistic users in the context of AI-assisted communication
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
