Grounding Language in Bodily States: The Case for Emotion
Abstract
It has become increasingly clear over the past few years that the symbols used by language become meaningful through grounding. For example, Glenberg and Kaschak (2002) demonstrated that some linguistic constructions are grounded in literal action, and Pecher, Zeelenberg, and Barsalou (2003), as well as Stanfield and Zwaan (2001), showed how language is grounded in perceptual and imaginal states, respectively. In this chapter, we report initial results demonstrating how language may also be grounded in the bodily states that comprise emotions. We begin by discussing the logical and theoretical reasons for supposing that language is grounded in bodily states, and then we move to a brief review of the recent work demonstrating grounding in action and perceptual states. This introductory material is followed by the report of two experiments consistent with the claim that language about emotional states is more completely understood when those states are literally embodied during comprehension. WHY LANGUAGE MUST BE GROUNDED OUTSIDE THE LINGUISTIC SYSTEM To ask how a symbol is grounded is to ask how it becomes meaningful by mapping it onto something else that is already meaningful. One hypothesis is that linguistic symbols (e.g., words and syntactic constructions) become meaningful only when they are mapped to nonlinguistic experiences such as actions and perceptions. A second hypothesis is that linguistic symbols can be grounded in other linguistic symbols. For example, words are often defined in terms of other words: That is exactly how most dictionaries work.
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Grounding models in data other than linguistic descriptions of symptoms, such as objective behavioral or physiological signals, is another way of reducing variability in LLM performance, as words alone may not fully capture all of the necessary information to complete a given mental health task.
“Grounding models in data other than linguistic descriptions of symptoms (eg, objective behavioral or physiological signals) is another way of reducing variability in LLM performance, as words alone may not fully capture all of the necessary information to complete a given mental health task [67].”
From The Opportunities and Risks of Large Language Models in Mental Health (2024) · cites this paper as [67]
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- Authors
- Glenberg, A. M., Havas, D., Becker, R., & Rinck, M.
- Affiliations
- University of Wisconsin–Madison (US)
- Technische Universität Dresden (DE)
- ORCID
- Glenberg, Arthur M.
- Venue
- Grounding Cognition
- Publisher
- Cambridge University Press
- Published
- 2005-01-10
- Pages
- 115-128
- OpenAlex
- W1507779396
- Cited by
- 123
- References
- 30
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 4 · 2023: 2 · 2022: 5 · 2021: 3 · 2020: 5 · 2019: 4 · 2018: 2 · 2017: 9 · 2016: 6 · 2015: 9 · 2014: 5 · 2013: 8 · 2012: 14
- FWCI
- 15.38
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Language, Metaphor, and Cognition
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- language grounding, emotions, bodily states, embodied cognition, perceptual grounding, semantic representation, word meaning
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