Scholarlink

<p>Analysis and generation of conversational gestures, especially in multi-party settings, remains an open challenge in many fields, due to the lack of publicly available datasets, models, and standardized evaluation metrics. To address this gap, we introduce <i>Multi-TPC</i>, a multimodal dataset of three-party conversations featuring synchronized speech, motion, and gaze. Multi-TPC captures rich conversational dynamics, enabling the study of interactions between multiple participants. Our statistical analysis reveals correlations between gestures and various modalities, including audio, text, and speaker identity. Our dataset and model provide a foundation for advancing research in discourse analysis, human communication dynamics, and multimodal interaction.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Multi-TPC: A Multimodal Dataset for Three-Party Conversations with Speech, Motion, and Gaze

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月12日

查看全文
  • Meng-Chen Lee,
  • Zhigang Deng

摘要

Analysis and generation of conversational gestures, especially in multi-party settings, remains an open challenge in many fields, due to the lack of publicly available datasets, models, and standardized evaluation metrics. To address this gap, we introduce Multi-TPC, a multimodal dataset of three-party conversations featuring synchronized speech, motion, and gaze. Multi-TPC captures rich conversational dynamics, enabling the study of interactions between multiple participants. Our statistical analysis reveals correlations between gestures and various modalities, including audio, text, and speaker identity. Our dataset and model provide a foundation for advancing research in discourse analysis, human communication dynamics, and multimodal interaction.