Leveraging Acoustic and Motion Signals for Detecting Topic Transitions in VR Meetings

• Item type: National Convention(1)
• 公開日: 2024-03-01
• タイトル: Leveraging Acoustic and Motion Signals for Detecting Topic Transitions in VR Meetings
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: ネットワーク
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: 九大
• 著者所属: 九大
• 著者所属: 九大
• 著者所属: 九大
• 著者所属: 九大
• 著者名: Zhankun, Liu; 陳, 家東; Chenghao, Gu; 張, 佳儀; 木實, 新一
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: With the proliferation of consumer-grade VR devices, remote meetings within virtual environments are becoming increasingly popular. Meeting segmentation can swiftly offer users a valuable, advanced understanding of past meeting discourse while enhancing team communication efficiency in virutual environments. Detecting topic Transitions within VR-based meeting, however, is an extremely difficult task due to the hinderance of non-verval communication in virtual environments. This paper explores the correlation between topic transitions, acoustic features, and changes in bodily posture in virtual environments, and proposes a novel approach that combines acoustic features and posture data for dialogue topic segmentation.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00349328
• 書誌情報: 第86回全国大会講演論文集; 巻 2024, 号 1, p. 409-410, 発行日 2024-03-01
• 出版者 / 言語: ja
• 出版者: 情報処理学会