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

TL;DR

AffectAI-Capture is a standardized, reproducible protocol for collecting multimodal data in small-group meetings, enabling comprehensive affective and behavioral analysis.

Contribution

It introduces a reproducible protocol architecture that integrates task design, instrumentation, synchronization, and data organization for meeting research.

Findings

Validated audio quality and video synchronization through bench tests.

Established a standardized data collection and processing framework.

Ongoing collection with full validation pending.

Abstract

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 task blocks grounded in established group-interaction paradigms, while acquisition and post-processing are organized around a single authoritative event timeline and standardized outputs. We describe the experimental rationale, synchronization philosophy, data organization, and practical trade-offs. Pilot-level validation of audio quality and video synchronization has been conducted using controlled bench tests; full protocol sessions with participants remain ongoing work. The contribution is a reproducible protocol architecture linking task design, instrumentation, timing provenance, and data packaging for affective, behavioral, and meeting-analytics research.