WordDecipher：利用面向非英语母语者的可解释AI增强数字工作空间沟通
WordDecipher: Enhancing Digital Workspace Communication with Explainable AI for Non-native English Speakers
AI总结：
本文提出可解释AI写作工具WordDecipher，结合LLM与词嵌入识别社交意图、生成贴合意图的改写建议并解释表达差异，以帮助非英语母语者改善职场文本沟通。
摘要：
非英语母语者（NNES）在数字工作空间沟通（例如电子邮件、Slack消息）中面临挑战，他们常常会无意中把母语中的表达直译过来，从而导致表达生硬或错误。现有的AI辅助写作工具具备流畅度增强和改写建议功能；然而，NNES可能难以把握不同表达之间的细微差别，因此很难选择能够准确反映其意图的表达。在高风险的基于文本的沟通中，这类挑战会进一步加剧，因为缺少非语言线索会增加误解的风险。借助大语言模型（LLM）和词嵌入的最新进展，我们提出了WordDecipher，这是一款可解释的AI辅助写作工具，旨在增强NNES的数字工作空间沟通。WordDecipher不仅能识别在用户写作中检测到的、被感知到的社交意图，还能生成与用户预期信息相符的改写建议，这些预期信息可通过数值方式给出，或从用户以母语撰写的内容中推断得出。随后，WordDecipher会提供细微差别的概览，以帮助NNES进行选择。通过一个使用场景，我们展示了WordDecipher如何显著提升NNES传达其请求的能力，展现了其改变NNES工作空间沟通的潜力。
英文摘要：
Non-native English speakers (NNES) face challenges in digital workspace communication (e.g., emails, Slack messages), often inadvertently translating expressions from their native languages, which can lead to awkward or incorrect usage. Current AI-assisted writing tools are equipped with fluency enhancement and rewriting suggestions; however, NNES may struggle to grasp the subtleties among various expressions, making it challenging to choose the one that accurately reflects their intent. Such challenges are exacerbated in high-stake text-based communications, where the absence of non-verbal cues heightens the risk of misinterpretation. By leveraging the latest advancements in large language models (LLM) and word embeddings, we propose WordDecipher, an explainable AI-assisted writing tool to enhance digital workspace communication for NNES. WordDecipher not only identifies the perceived social intentions detected in users' writing, but also generates rewriting suggestions aligned with users' intended messages, either numerically or by inferring from users' writing in their native language. Then, WordDecipher provides an overview of nuances to help NNES make selections. Through a usage scenario, we demonstrate how WordDecipher can significantly enhance an NNES's ability to communicate her request, showcasing its potential to transform workspace communication for NNES.
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。
