Résumé
This exploratory study addresses the challenges of evaluating the quality of hand-gesture synthesis. It introduces an interdisciplinary methodology aimed at providing objective evaluation criteria. The study examines expert annotations applied on a small dataset combining both natural and synthetic gestures, showing how their comparison can reveal key indicators for assessing communicative efficiency and adequate movement dynamics. Communicative gestures are more frequent, shorter, and easier to interpret in natural data, while synthetic gestures are more ambiguous, with less precise annotations and less consistent velocity profiles. These findings support the idea that only an interdisciplinary approach -combining computational modeling with insights from gesture studies in the language sciences-can yield meaningful criteria for evaluating and ultimately improving the quality of synthesized gestures.