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Research

We study the cognitive processes that underlie language use, and build detailed models of these mechanisms so they can be implemented in computational models. Our research covers the three domains of linguistic knowledge - meaning, form, and the relation between them.

Simulation Semantics

What does it mean to understand a piece of language, and what is the nature of the meanings of words and other linguistic elements? Our experimental and theoretical work on Simulation Semantics argues that in order to produce or understand meaningful language, language users run a mental simulation of (that is, mentally imagine) the content of utterances. Running this simulation involves activating the same neural structures that are responsible for perceiving or performing the events described in the utterance, in effect, recreating the internal states associated with perceiving described scenes or performing described actions.

For instance, in understanding a sentence like Mary tossed me a drink, one creates a mental image or simulation of what the scene looks like (size, shape, orientation, trajectory of the drink) and/or what is required to execute the actions involved (body parts used, the amount of force exerted, etc.).

The idea that language drives mental simulation explains

  • how linguistic meaning can be related to previous, grounded experiences and thus deeply understood (such as previous instances of drink-tossing.)
  • how language users can quickly produce appropriate physical responses (like checking to see if the speaker still has the drink, or maybe a stain on his shirt)
  • how understanders automatically make detailed inferences (like that the beverage container was closed, that the drink was perhaps alcoholic, and so on)

Further reading: Experimental methods for simulation semantics. 2007. in Monica Gonzalez-Marquez, Irene Mittelberg, Seana Coulson, and Michael J. Spivey (eds.) Methods in Cognitive Linguistics: Ithaca. John Benjamins.
 
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Phonaesthemes

What are the primitive units that pair form and meaning? Traditionally, this is the role of morphemes, like cat, run and the plural -s. But there exist other correlations in form and meaning that are not compositional and thus are not classical morphemes. These correlations are called phonaesthemes - frequently recurring sound-meaning pairings that are not contrastive morphemes. An example is the English onset gl-, which, like other phonaesthemes, is relatively infrequent in English, except among words with meanings related to VISION and LIGHT, like glimmer, glisten, glow, glimpse and many others. Another well-documented phonaestheme is the English onset sn-, which occurs in a large number of words relating to MOUTH and NOSE, like snore, snack, snout, snarl, and others.

Our experimental work on phonaesthemes shows that not only are phonaesthemes used during language processing, (as seen through priming experiments) but in addition they display priming effects that are very similar to those produced by classical productive morphemes. We conclude from this that form meaning pairings within words are represented as part of the linguistic system, even if they are not morphological.

Bergen, Benjamin, 2004. The psychological reality of phonaesthemes. Language 80(2).
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Embodied Construction Grammar

Along with colleagues at UC Berkeley and elsewhere, we have been developing a model of language representation and use called Embodied Construction Grammar (ECG). ECG includes a computationally precise formalism, but unlike other formal models, is also cognitively oriented in a number of ways.
  • Like other Construction and Cognitive Grammars, semantics is tightly integrated with linguistic form in the grammar
  • Linguistic semantics is grounded in cognitive processes
  • Its formalism is grounded in how the brain processes information.
  • Meaning, context, discourse function, and domain-general cognitive mechanisms such as metaphor and metonymy are fully integrated into the grammar
  • The theory presupposes no competence-performance distinction.
  • The formalism is explicit enough to be used in practical computer applications it has already been used for functions like parsing, grammar learning, and language understanding.
Bergen, Benjamin and Nancy Chang. 2005. Embodied Construction Grammar in Simulation-Based Language Understanding. In Jan-Ola Ostman and Miriam Fried (Eds.), Construction Grammars: Cognitive grounding and theoretical extensions.
 
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