Many meetings require creating a meeting summary to keep everyone up to date. Creating minutes of sufficient quality is however very cognitively demanding. Although we currently possess capable models for both audio speech recognition (ASR) and summarization, their fully automatic use is still problematic. ASR models frequently commit errors when transcribing named entities while the summarization models tend to hallucinate and misinterpret the transcript. We propose a novel tool -- Minuteman -- to enable efficient semi-automatic meeting minuting. The tool provides a live transcript and a live meeting summary to the users, who can edit them in a collaborative manner, enabling correction of ASR errors and imperfect summary points in real time. The resulting application eases the cognitive load of the notetakers and allows them to easily catch up if they missed a part of the meeting due to absence or a lack of focus. We conduct several tests of the application in varied settings, exploring the worthiness of the concept and the possible user strategies.

翻译：许多会议需要生成会议摘要以保持所有参与者信息同步。然而，制作高质量的会议纪要仍是一项认知负荷极高的任务。尽管当前已拥有高性能的音频语音识别（ASR）与摘要生成模型，但完全自动化应用仍存在显著问题：ASR模型在转写命名实体时频繁出错，而摘要模型则倾向于产生幻觉并曲解转录内容。本文提出一种新型工具——Minuteman——以实现高效半自动会议纪要生成。该工具为用户提供实时转录文本与实时会议摘要，支持用户以协同编辑方式实时修正ASR错误及不完善的摘要要点。该应用有效减轻了记录者的认知负担，并使其在因缺席或注意力分散错过会议片段时能便捷地回溯信息。我们通过多场景测试验证了该应用概念的可行性及潜在的用户使用策略。