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New protocol captures multimodal data for meeting research

Researchers have developed AffectAI-Capture, a new protocol designed for collecting synchronized multimodal data during small-group interactions. This protocol integrates various data streams, including eye tracking, physiological data from wearables, audio recordings, multi-view video, and self-reports. The aim is to provide a reproducible framework for research into affective and behavioral dynamics within meetings, with ongoing pilot validation. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Provides a standardized method for collecting rich data that could be used to train and evaluate AI systems for meeting analysis.

RANK_REASON The cluster contains a new academic paper detailing a research protocol. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Andrew Burke Dittberner ·

    AffectAI-Capture: A Reproducible Multimodal Protocol for Small-Group Meeting Research

    We present AffectAI-Capture, a protocol for collecting synchronized multimodal data in four-person meeting-like interactions, combining eye tracking, wearable physiology, close-talk and room audio, multi-view video, event logging, and structured self-report. Sessions use fixed ta…