Final Report Summary - UNIVERSAL (A Universal Model of Word Comprehension)
The aim of this project was to evaluate the cross-linguistic differences associated with visual and auditory word recognition, and how these representations map onto word meaning. Overall, this work has revealed that a number off prior published models and theories are not theories of language in general, but rather are theories of English in particular. This work has helped to highlight important aspects of the visual and auditory word recognition systems that are flexible and are able to adapt to the specific constraints imposed by each language. For example, we have shown how cross-linguistic differences in the number of anagrams in Hebrew versus in English explain why differential sensitivity emerges for identifying the position of letters in each language. We have also shown that the degree of information flow between auditory and visual word representations is mediated by the spelling-sound and sound spelling consistency between the languages, as assessed in English, French, and Spanish.
In addition to this work on cross-linguistic differences, we have also conducted two main extensions of the original proposal. One of these extensions was to connect our work on language with the broader research on statistical learning of regularities across space and time. This work has helped highlight now the differences that emerge between visual and auditory word processing may not be due to language processing per se, but may instead be attributable to domain-general processing mechanisms that are interacting with modality specific constraints.
Furthermore, this project has helped connect studies of language to computational models not only at the behavioral level, but also at a more detailed and mechanistically explicit level in terms of the online measurement of the neural correlates of language processing. Consequently, the resulting theories and models offer an unprecedented unifying account of various aspects of language processing, which are suitable for integration of future findings from a wide area of research and for extensions to other related systems (e.g. episodic memory, semantic memory).
In addition to this work on cross-linguistic differences, we have also conducted two main extensions of the original proposal. One of these extensions was to connect our work on language with the broader research on statistical learning of regularities across space and time. This work has helped highlight now the differences that emerge between visual and auditory word processing may not be due to language processing per se, but may instead be attributable to domain-general processing mechanisms that are interacting with modality specific constraints.
Furthermore, this project has helped connect studies of language to computational models not only at the behavioral level, but also at a more detailed and mechanistically explicit level in terms of the online measurement of the neural correlates of language processing. Consequently, the resulting theories and models offer an unprecedented unifying account of various aspects of language processing, which are suitable for integration of future findings from a wide area of research and for extensions to other related systems (e.g. episodic memory, semantic memory).