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Research into the multimodal dimensions of human communication faces a set of distinctive methodological challenges. Collecting the datasets is resource-intensive, analysis often lacks peer validation, and the absence of shared datasets makes it difficult to develop standards. External validity is hampered by small datasets, yet large datasets are intractable. Red Hen Lab spearheads an international infrastructure for data-driven multimodal communication research, facilitating an integrated cross-disciplinary workflow. Linguists, communication scholars, statisticians, and computer scientists work together to develop research questions, annotate training sets, and develop pattern discovery and machine learning tools that handle vast collections of multimodal data, beyond the dreams of previous researchers. This infrastructure makes it possible for researchers at multiple sites to work in real-time in transdisciplinary teams. We review the vision, progress, and prospects of this research consortium.

Toward an infrastructure for data-driven multimodal communication research