When Does a Laugh Begin? Structured Annotator Disagreement in Temporal Laughter Localization

Title:When Does a Laugh Begin? Structured Annotator Disagreement in Temporal Laughter Localization

Abstract:Annotators routinely disagree on laughter boundaries and subtle chuckles, yet temporal laughter localization typically evaluates against a single reference annotation. We show that this disagreement is structured rather than random noise. Re-annotating the SMILE-Temporal benchmark (672 videos, 1,683 events) with 3-5 annotators per video (alpha = 0.757), we find systematic patterns: disagreement is 1.73 times larger at offsets than onsets, far more common for chuckles than full laughs (77% vs. 20%), and predictable from event attributes (AUC = 0.831). Evaluating against a single annotator breaks down under this structure: system scores shift by 0.246 F1 depending on the chosen ground truth, correctly ranking systems only 69.7% of the time (vs. 80% against all annotators). We propose a disagreement-calibrated evaluation that scores predictions against the full annotator distribution using conformally calibrated tolerance bands (wider at offsets, 0.727s, than onsets, 0.5s). The per-annotator annotations and analysis code are available at this https URL .

Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI)

arXiv:2609.06646 [cs.CV]

(or arXiv:2609.06646v1 [cs.CV] for this version)

https://doi.org/10.48550/arXiv.2609.06646 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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