ArticleLanguage, cognition and neuroscience2023
Speakers prioritise affordance-based object semantics in scene descriptions.
Article in Language, cognition and neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The Cross-Linguistic Coordination of Overt Attention and Speech Production as Evidence for a Language of Vision.Cognitive science · 2026Article
- Planning to be incremental: Scene descriptions reveal meaningful clustering in language production.Cognition · 2026Article
- Perceptual Clauses as Units of Production in Visual Descriptions.Topics in cognitive science · 2025Article
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Authors and funding
3 authors.
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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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.