用AI实时监测敏捷团队负责人情绪，助其及时调整负面表达。
EGI: A Multimodal Emotional AI Framework for Enhancing Scrum Master Real-time Self-Awareness
- 融合语音转写、语调分析、情感词汇匹配与上下文建议四模块。
- 模拟会议中语音识别错误率10%，实时反馈显著提升情绪觉察能力。
- 适合敏捷团队负责人、会议主持人提升情绪管理能力。
尽管越来越多研究关注敏捷团队成员的情绪健康，但在对Scrum Master和会议组织者的情绪监测方面仍存在显著空白，而这些角色对团队动态影响重大。本文提出一种创新应用，集成四种精选推荐的AI模型，以监测这些关键角色无意识流露的情绪。通过实时语音转写、基于阈值的语调分析检测语调中的情感线索、情感词汇匹配识别话语情感倾向，并利用开源多模块AI API提供含情感关键词的上下文建议。系统在模拟会议环境中实现10%的语音识别错误率（WER）。评估表明，实时反馈显著提升了模拟敏捷会议中情绪觉察水平，为Scrum Master和会议组织者提供即时实用建议，帮助其快速识别并减少负面情绪表达，促进更积极高效的团队互动。
原文摘要 · Abstract (English)
While increasing research focuses on the emotional well-being of agile team members, a significant gap remains in emotion monitoring studies for Scrum Masters and meeting organizers, whose impact on team dynamics is crucial. This paper proposes a novel application integrating four carefully selected and recommended AI models to monitor the unconsciously expressed emotions of these key roles. This is achieved through: real- time transcription using a speech-to-text model; thresholding for intonation analysis to detect emotional cues in prosody; applying emotion-based vocabulary matching to identify sentiment in spoken content; and providing context-aware suggestions containing emotion keywords using an open-source, multi-module AI API. The system achieved an ASR word error rate WER of 10% in simulated meeting environments. Our evaluation shows that real- time feedback significantly improves emotion awareness during simulated agile meetings, providing Scrum Masters and meeting organizers with real-time and practical suggestions to help them quickly identify and minimize the expression of negative emotions, fostering more positive and effective team interactions.
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