This study forms continuous recognition of the Group Emotion at a one-second resolution, introduces the Mixed state, which captures the emotional divergence among participants in the group, and proposes a multimodal temporal framework that integrates audio and video information using a sliding-window context.
Soma Iwata, K. Inoue, Mu-Yun Wu et al.· 0 citations
This paper describes the collection design, participants, recording setup, transcription format, and corpus statistics, and provides preliminary analyses to illustrate how TEIDAN can support research on turn-taking, addressee recognition, and multimodal grounding in human-human and human-agent interaction.
Taiga Mori, K. Inoue, Mikey Elmers et al.· 1 citation
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