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TEIDAN introduces a new multilingual multimodal corpus designed specifically for spontaneous, face-to-face triadic discussions in Japanese and English. By capturing fine-grained audio-visual data from three participants, this resource directly addresses the scarcity of datasets needed to train agents capable of handling complex group dynamics and cross-linguistic turn-taking. This advancement is critical for developing next-generation human-agent interaction systems that can naturally participate in informal social settings rather than just structured meetings.
TEIDAN: A Multilingual Multiparty Dialogue Corpus
arXiv:2609.00802v1 Announce Type: new Abstract: Multi-party interaction is a central setting for human communication and a necessary target for human-agent interaction systems that must participate in group conversation. Yet available corpora often focus on meetings, task-oriented interaction, text-based interaction, or acted scenarios, and fewer resources support cross-linguistic comparison of spontaneous face-to-face triadic discussion. This paper presents TEIDAN, a multilingual multimodal corpus that currently consists of Japanese and English three-party conversations. TEIDAN records groups of three participants discussing open-ended topics with individual pin microphones, a microphone array, and participant-facing cameras, and provides IPU-based transcripts for both language portions. Earlier studies used subsets of the Japanese portion for task-specific benchmarks in multi-party dialogue modeling; in contrast, this paper presents TEIDAN as a corpus resource spanning both Japanese and English, with planned expansion to additional languages. We describe the collection design, participants, recording setup, transcription format, and corpus statistics, and provide preliminary analyses to illustrate how TEIDAN can support research on turn-taking, addressee recognition, and multimodal grounding in human-human and human-agent interaction.
Abstract:Multi-party interaction is a central setting for human communication and a necessary target for human-agent interaction systems that must participate in group conversation. Yet available corpora often focus on meetings, task-oriented interaction, text-based interaction, or acted scenarios, and fewer resources support cross-linguistic comparison of spontaneous face-to-face triadic discussion. This paper presents TEIDAN, a multilingual multimodal corpus that currently consists of Japanese and English three-party conversations. TEIDAN records groups of three participants discussing open-ended topics with individual pin microphones, a microphone array, and participant-facing cameras, and provides IPU-based transcripts for both language portions. Earlier studies used subsets of the Japanese portion for task-specific benchmarks in multi-party dialogue modeling; in contrast, this paper presents TEIDAN as a corpus resource spanning both Japanese and English, with planned expansion to additional languages. We describe the collection design, participants, recording setup, transcription format, and corpus statistics, and provide preliminary analyses to illustrate how TEIDAN can support research on turn-taking, addressee recognition, and multimodal grounding in human-human and human-agent interaction.
8 pages, 1 figure, 3 tables. To appear in the Companion Proceedings of the 28th ACM International Conference on Multimodal Interaction (ICMI Companion '26)
Computation and Language (cs.CL); Human-Computer Interaction (cs.HC)
arXiv:2609.00802 [cs.CL]
(or arXiv:2609.00802v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.00802 arXiv-issued DOI via DataCite (pending registration)
https://doi.org/10.1145/3776591.3836650 DOI(s) linking to related resources
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