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Updated: Jul 13, 2025

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Published on: November 30, 2018
Speakers prioritise affordance-based object semantics in scene descriptions
M Barker1, G Rehrig1, F Ferreira1
1Department of Psychology, University of California, Davis.
Abstract:
This work investigates the linearisation strategies used by speakers when describing real-world scenes to better understand production plans for multi-utterance sequences. In this study, 30 participants described real-world scenes aloud. To investigate which semantic features of scenes predict order of mention, we quantified three features (meaning, graspability, and interactability) using two techniques (whole-object ratings and feature map values). We found that object-level semantic features, namely those affordance-based, predicted order of mention in a scene description task. Our findings provide the first evidence for an object-related semantic feature that guides linguistic ordering decisions and offer theoretical support for the role of object semantics in scene viewing and description.
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